IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Perceptual Weights Based On Local Energy For Image Quality AssessmentCSCJournals
This paper proposes an image quality metric that can effectively measure the quality of an image that correlates well with human judgment on the appearance of the image. The present work adds a new dimension to the structural approach based full-reference image quality assessment for gray scale images. The proposed method assigns more weight to the distortions present in the visual regions of interest of the reference (original) image than to the distortions present in the other regions of the image, referred to as perceptual weights. The perceptual features and their weights are computed based on the local energy modeling of the original image. The proposed model is validated using the image database provided by LIVE (Laboratory for Image & Video Engineering, The University of Texas at Austin) based on the evaluation metrics as suggested in the video quality experts group (VQEG) Phase I FR-TV test.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
A Novel Feature Extraction Scheme for Medical X-Ray ImagesIJERA Editor
X-ray images are gray scale images with almost the same textural characteristic. Conventional texture or color
features cannot be used for appropriate categorization in medical x-ray image archives. This paper presents a
novel combination of methods like GLCM, LBP and HOG for extracting distinctive invariant features from Xray
images belonging to IRMA (Image Retrieval in Medical applications) database that can be used to perform
reliable matching between different views of an object or scene. GLCM represents the distributions of the
intensities and the information about relative positions of neighboring pixels of an image. The LBP features are
invariant to image scale and rotation, change in 3D viewpoint, addition of noise, and change in illumination A
HOG feature vector represents local shape of an object, having edge information at plural cells. These features
have been exploited in different algorithms for automatic classification of medical X-ray images. Excellent
experimental results obtained in true problems of rotation invariance, particular rotation angle, demonstrate that
good discrimination can be achieved with the occurrence statistics of simple rotation invariant local binary
patterns.
Fuzzy Region Merging Using Fuzzy Similarity Measurement on Image Segmentation IJECEIAES
Some image’s regions have unbalance information, such as blurred contour, shade, and uneven brightness. Those regions are called as ambiguous regions. Ambiguous region cause problem during region merging process in interactive image segmentation because that region has double information, both as object and background. We proposed a new region merging strategy using fuzzy similarity measurement for image segmentation. The proposed method has four steps; the first step is initial segmentation using mean-shift algorithm. The second step is giving markers manually to indicate the object and background region. The third step is determining the fuzzy region or ambiguous region in the images. The last step is fuzzy region merging using fuzzy similarity measurement. The experimental results demonstrated that the proposed method is able to segment natural images and dental panoramic images successfully with the average value of misclassification error (ME) 1.96% and 5.47%, respectively.
Importance of Mean Shift in Remote Sensing SegmentationIOSR Journals
1) Mean shift is a non-parametric clustering technique that can segment remote sensing images into homogeneous regions without prior knowledge of the number of clusters or constraints on cluster shape.
2) The document presents a case study demonstrating mean shift can segment an image containing oil storage tanks into distinct regions faster than level set segmentation.
3) Mean shift is shown to be well-suited for remote sensing image segmentation tasks like forest mapping and land cover classification due to its ability to handle noise, gradients, and texture variations common in real-world images.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Journals
This document summarizes an article that presents a method for implementing image segmentation using edge detection based on the Sobel edge operator on an FPGA. It describes how the Sobel operator works by calculating horizontal and vertical gradients to detect edges. The document outlines the steps to segment an image using Sobel edge detection, including applying horizontal and vertical masks, calculating the gradient, and thresholding. It also provides the architecture for the FPGA implementation, including modules for pixel generation, Sobel enhancement, edge detection, and binary segmentation. The results show edge detection outputs from MATLAB and simulation waveforms, demonstrating the FPGA-based method can perform edge-based image segmentation.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document presents a new interactive image segmentation method called Advanced Maximal Similarity Based Region Merging (MSRM) using user interactions. The method first segments the image using multi-level thresholding. The user then marks regions of the desired object with markers. Regions are represented by color histograms and similarity is measured using Euclidean distance of mean color values. Regions are merged based on similarity, first merging marked and unmarked object regions, then merging remaining unmarked regions. Results show the proposed MSRM method achieves higher true positive rates and lower false positive rates than other interactive segmentation methods.
Perceptual Weights Based On Local Energy For Image Quality AssessmentCSCJournals
This paper proposes an image quality metric that can effectively measure the quality of an image that correlates well with human judgment on the appearance of the image. The present work adds a new dimension to the structural approach based full-reference image quality assessment for gray scale images. The proposed method assigns more weight to the distortions present in the visual regions of interest of the reference (original) image than to the distortions present in the other regions of the image, referred to as perceptual weights. The perceptual features and their weights are computed based on the local energy modeling of the original image. The proposed model is validated using the image database provided by LIVE (Laboratory for Image & Video Engineering, The University of Texas at Austin) based on the evaluation metrics as suggested in the video quality experts group (VQEG) Phase I FR-TV test.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
A Novel Feature Extraction Scheme for Medical X-Ray ImagesIJERA Editor
X-ray images are gray scale images with almost the same textural characteristic. Conventional texture or color
features cannot be used for appropriate categorization in medical x-ray image archives. This paper presents a
novel combination of methods like GLCM, LBP and HOG for extracting distinctive invariant features from Xray
images belonging to IRMA (Image Retrieval in Medical applications) database that can be used to perform
reliable matching between different views of an object or scene. GLCM represents the distributions of the
intensities and the information about relative positions of neighboring pixels of an image. The LBP features are
invariant to image scale and rotation, change in 3D viewpoint, addition of noise, and change in illumination A
HOG feature vector represents local shape of an object, having edge information at plural cells. These features
have been exploited in different algorithms for automatic classification of medical X-ray images. Excellent
experimental results obtained in true problems of rotation invariance, particular rotation angle, demonstrate that
good discrimination can be achieved with the occurrence statistics of simple rotation invariant local binary
patterns.
Fuzzy Region Merging Using Fuzzy Similarity Measurement on Image Segmentation IJECEIAES
Some image’s regions have unbalance information, such as blurred contour, shade, and uneven brightness. Those regions are called as ambiguous regions. Ambiguous region cause problem during region merging process in interactive image segmentation because that region has double information, both as object and background. We proposed a new region merging strategy using fuzzy similarity measurement for image segmentation. The proposed method has four steps; the first step is initial segmentation using mean-shift algorithm. The second step is giving markers manually to indicate the object and background region. The third step is determining the fuzzy region or ambiguous region in the images. The last step is fuzzy region merging using fuzzy similarity measurement. The experimental results demonstrated that the proposed method is able to segment natural images and dental panoramic images successfully with the average value of misclassification error (ME) 1.96% and 5.47%, respectively.
Importance of Mean Shift in Remote Sensing SegmentationIOSR Journals
1) Mean shift is a non-parametric clustering technique that can segment remote sensing images into homogeneous regions without prior knowledge of the number of clusters or constraints on cluster shape.
2) The document presents a case study demonstrating mean shift can segment an image containing oil storage tanks into distinct regions faster than level set segmentation.
3) Mean shift is shown to be well-suited for remote sensing image segmentation tasks like forest mapping and land cover classification due to its ability to handle noise, gradients, and texture variations common in real-world images.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Journals
This document summarizes an article that presents a method for implementing image segmentation using edge detection based on the Sobel edge operator on an FPGA. It describes how the Sobel operator works by calculating horizontal and vertical gradients to detect edges. The document outlines the steps to segment an image using Sobel edge detection, including applying horizontal and vertical masks, calculating the gradient, and thresholding. It also provides the architecture for the FPGA implementation, including modules for pixel generation, Sobel enhancement, edge detection, and binary segmentation. The results show edge detection outputs from MATLAB and simulation waveforms, demonstrating the FPGA-based method can perform edge-based image segmentation.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document presents a new interactive image segmentation method called Advanced Maximal Similarity Based Region Merging (MSRM) using user interactions. The method first segments the image using multi-level thresholding. The user then marks regions of the desired object with markers. Regions are represented by color histograms and similarity is measured using Euclidean distance of mean color values. Regions are merged based on similarity, first merging marked and unmarked object regions, then merging remaining unmarked regions. Results show the proposed MSRM method achieves higher true positive rates and lower false positive rates than other interactive segmentation methods.
Image Segmentation Using Pairwise Correlation ClusteringIJERA Editor
A pairwise hypergraph based image segmentation framework is formulated in a supervised manner for various images. The image segmentation is to infer the edge label over the pairwise hypergraph by maximizing the normalized cuts. Correlation clustering which is a graph partitioning algorithm, was shown to be effective in a number of applications such as identification, clustering of documents and image segmentation.The partitioning result is derived from a algorithm to partition a pairwise graph into disjoint groups of coherent nodes. In the pairwise correlation clustering, the pairwise graph which is used in the correlation clustering is generalized to a superpixel graph where a node corresponds to a superpixel and a link between adjacent superpixels corresponds to an edge. This pairwise correlation clustering also considers the feature vector which extracts several visual cues from a superpixel, including brightness, color, texture, and shape. Significant progress in clustering has been achieved by algorithms that are based on pairwise affinities between the datasets. The experimental results are shown by calculating the typical cut and inference in an undirected graphical model and datasets.
OBJECT SEGMENTATION USING MULTISCALE MORPHOLOGICAL OPERATIONSijcseit
Object segmentation plays an important role in human visual perception, medical image processing and content based image retrieval. It provides information for recognition and interpretation. This paper uses mathematical morphology for image segmentation. Object segmentation is difficult because one usually does not know a priori what type of object exists in an image, how many different shapes are there and what regions the image has. To carryout discrimination and segmentation several innovative segmentation methods, based on morphology are proposed. The present study proposes segmentation method based on multiscale morphological reconstructions. Various sizes of structuring elements have been used to segment simple and complex shapes. It enhances local boundaries that may lead to improve segmentation accuracy.The method is tested on various datasets and results shows that it can be used for both interactive and automatic segmentation.
Amalgamation of contour, texture, color, edge, and spatial features for effic...eSAT Journals
Abstract From the past few years, Content based image retrieval (CBIR) has been a progressive and curious research area. Image retrieval is a process of extraction of the set of images from the available image database resembling the query image. Many CBIR techniques have been proposed for relevant image recoveries. However most of them are based on a particular feature extraction like texture based recovery, color based retrieval system etc. Here in this paper we put forward a novel technique for image recovery based on the integration of contour, texture, color, edge, and spatial features. Contourlet decomposition is employed for the extraction of contour features such as energy and standard deviation. Directionality and anisotropy are the properties of contourlet transformation that makes it an efficient technique. After feature extraction of query and database images, similarity measurement techniques such as Squared Euclidian and Manhattan distance were used to obtain the top N image matches. The simulation results in Matlab show that the proposed technique offers a better image retrieval. Satisfactory precision-recall rate is also maintained in this method. Keywords: Contourlet Decomposition, Local Binary Pattern, Squared Euclidian Distance, Manhattan Distance
Object recognition from image using grid based color moments feature extracti...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document summarizes a research paper that proposes an algorithm for detecting brain tumors in MRI images based on analyzing bilateral symmetry. The algorithm first performs preprocessing like smoothing and contrast enhancement. It then identifies the bilateral symmetry axis of the brain. Next, it segments the image into symmetric regions, enhancing asymmetric edges that may indicate a tumor. Experiments showed the algorithm can automatically detect tumor positions and boundaries. The algorithm leverages the fact that brain MRI of a healthy person is nearly bilaterally symmetric, while a tumor disrupts this symmetry.
Content-based Image Retrieval Using The knowledge of Color, Texture in Binary...Zahra Mansoori
This document presents a new approach for content-based image retrieval that combines color, texture, and a binary tree structure to describe images and their features. Color histograms in HSV color space and wavelet texture features are extracted as low-level features. A binary tree partitions each image into regions based on color and represents higher-level spatial relationships. The performance of the proposed system is evaluated on a subset of the COREL image database and compared to the SIMPLIcity image retrieval system. Experimental results show the proposed system has better retrieval performance than SIMPLIcity in some categories and comparable performance in others.
This document describes an interactive multi-label image segmentation algorithm called "GrowCut" based on cellular automata. The algorithm can segment N-dimensional images with multiple labels. With modest user input of labeled pixels, GrowCut automatically segments the rest of the image in an iterative process. It requires less user effort than other techniques for moderately difficult images. The algorithm has advantages such as efficiency, parallelizability, and extensibility to generate new segmentation methods.
This document provides a review of various texture classification approaches and texture datasets. It begins with an introduction to texture classification and its general framework. Key steps in texture classification are preprocessing, feature extraction, and classification. The document then discusses several common feature extraction methods used in texture classification, including local binary pattern (LBP), scale invariant feature transform (SIFT), speeded up robust features (SURF), Fourier transformation, texture spectrum, and gray level co-occurrence matrix (GLCM). It also reviews three popular classifiers for texture classification: K-nearest neighbors (K-NN), artificial neural network (ANN), and support vector machine (SVM). Finally, it mentions several popular texture datasets that are commonly used for training and testing texture
This document summarizes an evaluation of texture feature extraction methods for content-based image retrieval, including co-occurrence matrices, Tamura features, and Gabor filters. The evaluation tested these methods on a Corel image collection using Manhattan distance as the similarity measure. Co-occurrence matrices performed best with homogeneity as the feature, while Gabor wavelets showed better performance for homogeneous textures of fixed sizes. Tamura features performed poorly with directionality. Overall, co-occurrence matrices provided the best results for general texture retrieval.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
This paper proposes a novel technique for detecting point landmarks in 3D medical images based on phase congruency (PC). A bank of 3D log-Gabor filters is used to compute energy maps from the images. These energy maps are combined to form the PC measure, which is invariant to intensity variations and provides good feature localization. Significant 3D point landmarks are detected by analyzing the eigenvectors of PC moments computed at each point. The method is demonstrated on head and neck images for radiation therapy planning.
IRJET-A Review on Implementation of High Dimension Colour Transform in Domain...IRJET Journal
This document reviews algorithms for detecting salient regions in images using high dimensional color transforms. It summarizes several existing methods that use color contrast, frequency analysis, and superpixel segmentation. A key method discussed creates a saliency map by finding the optimal linear combination of color coefficients in a high dimensional color space. This allows more accurate detection of salient objects versus methods using only RGB color. The performance of this high dimensional color transform method is improved by also utilizing relative location and color contrast between superpixels as learned features.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
An Automatic Color Feature Vector Classification Based on Clustering MethodRSIS International
In computer vision application, visual features such as
shape, color and texture are extracted to characterize images.
Each of the features is represented using one or more feature
descriptors. One of the important requirements in image
retrieval, indexing, classification, clustering, etc. is extracting
efficient features from images. The color feature is one of the
most widely used visual features. Use of color histogram is the
most common way for representing color feature. One of
disadvantage of the color histogram is that it does not take the
color spatial distribution into consideration. In this paper an
automatic color feature vector classification based on clustering
approach is presented, which effectively describes the spatial
information of color features. The image retrieval results are
compare to improved color feature vector show the acceptable
efficiency of this approach. It propose an automatic color feature
vector classification of satellite images using clustering approach.
The intention is to study cluster a set of satellite images in several
categories on the color similarity basis. The images are processed
using LAB color space in the feature extraction stage. The
resulted color-based feature vectors are clustered using an
automatic unsupervised classification algorithm. Some
experiments based on the proposed recognition technique have
also been performed. More research, however, is needed to
identify and reduce uncertainties in the image processing chain
to improve classification accuracy. The mathematical training
and prediction analysis of a general familiarity with satellite
classifications meet typical map accuracy standards.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Color Particle Filter Tracking using Frame Segmentation based on JND Color an...IOSRJVSP
Object tracking is one of the most important components in numerous applications of computer vision. Color can provide an efficient visual feature for tracking non-rigid objects in real-time. The color is chosen as tracking feature to make the process scale and rotation invariant. The color of an object can vary over time due to variations in the illumination conditions, the visual angle and the camera parameters. This paper presents the integration of color distributions into particle filtering. The color feature is extracted using our novel 4D color histogram of the image, which is determined using JND color similarity threshold and connectivity of the neighboring pixels. Particle filter tracks several hypotheses simultaneously and weighs them according to their similarity to the target model. The popular Bhattacharyya coefficient is used as similarity measure between two color distributions. The tracking results are compared on the basis of precision over the data set of video sequences from the website http://visualtracking.net of CVPR13 bench marking paper. The proposed tracker yields better precision values as compared to previous reported results
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Vibration analysis and diagnostics for oil production units by pumping rodeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document summarizes a study on the heat transfer through a journal bearing. It describes the methodology used, which included collecting data on the bearing, performing design calculations, creating a geometric model, and conducting thermal analysis using FEA software. The analysis found that the bearing's temperature ranged from 79.76 to 90.96 degrees C, with most of the surface between 84-88 degrees C. It also determined that up to 14,328 watts of heat was generated within the bearing and up to 1,932 watts of heat was dissipated from the bearing casing through convection.
This document summarizes a research paper that proposes a parallel k-nearest neighbors (kNN) algorithm using OpenCL on a GPU architecture. The key points are:
1) kNN classification is computationally intensive, especially for large datasets, creating a need for parallelization.
2) The authors designed and implemented a parallel kNN algorithm using OpenCL to distribute distance computations across GPU cores.
3) Experimental results on UCI datasets showed the parallel kNN approach improved performance over a serial kNN implementation.
Image Segmentation Using Pairwise Correlation ClusteringIJERA Editor
A pairwise hypergraph based image segmentation framework is formulated in a supervised manner for various images. The image segmentation is to infer the edge label over the pairwise hypergraph by maximizing the normalized cuts. Correlation clustering which is a graph partitioning algorithm, was shown to be effective in a number of applications such as identification, clustering of documents and image segmentation.The partitioning result is derived from a algorithm to partition a pairwise graph into disjoint groups of coherent nodes. In the pairwise correlation clustering, the pairwise graph which is used in the correlation clustering is generalized to a superpixel graph where a node corresponds to a superpixel and a link between adjacent superpixels corresponds to an edge. This pairwise correlation clustering also considers the feature vector which extracts several visual cues from a superpixel, including brightness, color, texture, and shape. Significant progress in clustering has been achieved by algorithms that are based on pairwise affinities between the datasets. The experimental results are shown by calculating the typical cut and inference in an undirected graphical model and datasets.
OBJECT SEGMENTATION USING MULTISCALE MORPHOLOGICAL OPERATIONSijcseit
Object segmentation plays an important role in human visual perception, medical image processing and content based image retrieval. It provides information for recognition and interpretation. This paper uses mathematical morphology for image segmentation. Object segmentation is difficult because one usually does not know a priori what type of object exists in an image, how many different shapes are there and what regions the image has. To carryout discrimination and segmentation several innovative segmentation methods, based on morphology are proposed. The present study proposes segmentation method based on multiscale morphological reconstructions. Various sizes of structuring elements have been used to segment simple and complex shapes. It enhances local boundaries that may lead to improve segmentation accuracy.The method is tested on various datasets and results shows that it can be used for both interactive and automatic segmentation.
Amalgamation of contour, texture, color, edge, and spatial features for effic...eSAT Journals
Abstract From the past few years, Content based image retrieval (CBIR) has been a progressive and curious research area. Image retrieval is a process of extraction of the set of images from the available image database resembling the query image. Many CBIR techniques have been proposed for relevant image recoveries. However most of them are based on a particular feature extraction like texture based recovery, color based retrieval system etc. Here in this paper we put forward a novel technique for image recovery based on the integration of contour, texture, color, edge, and spatial features. Contourlet decomposition is employed for the extraction of contour features such as energy and standard deviation. Directionality and anisotropy are the properties of contourlet transformation that makes it an efficient technique. After feature extraction of query and database images, similarity measurement techniques such as Squared Euclidian and Manhattan distance were used to obtain the top N image matches. The simulation results in Matlab show that the proposed technique offers a better image retrieval. Satisfactory precision-recall rate is also maintained in this method. Keywords: Contourlet Decomposition, Local Binary Pattern, Squared Euclidian Distance, Manhattan Distance
Object recognition from image using grid based color moments feature extracti...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document summarizes a research paper that proposes an algorithm for detecting brain tumors in MRI images based on analyzing bilateral symmetry. The algorithm first performs preprocessing like smoothing and contrast enhancement. It then identifies the bilateral symmetry axis of the brain. Next, it segments the image into symmetric regions, enhancing asymmetric edges that may indicate a tumor. Experiments showed the algorithm can automatically detect tumor positions and boundaries. The algorithm leverages the fact that brain MRI of a healthy person is nearly bilaterally symmetric, while a tumor disrupts this symmetry.
Content-based Image Retrieval Using The knowledge of Color, Texture in Binary...Zahra Mansoori
This document presents a new approach for content-based image retrieval that combines color, texture, and a binary tree structure to describe images and their features. Color histograms in HSV color space and wavelet texture features are extracted as low-level features. A binary tree partitions each image into regions based on color and represents higher-level spatial relationships. The performance of the proposed system is evaluated on a subset of the COREL image database and compared to the SIMPLIcity image retrieval system. Experimental results show the proposed system has better retrieval performance than SIMPLIcity in some categories and comparable performance in others.
This document describes an interactive multi-label image segmentation algorithm called "GrowCut" based on cellular automata. The algorithm can segment N-dimensional images with multiple labels. With modest user input of labeled pixels, GrowCut automatically segments the rest of the image in an iterative process. It requires less user effort than other techniques for moderately difficult images. The algorithm has advantages such as efficiency, parallelizability, and extensibility to generate new segmentation methods.
This document provides a review of various texture classification approaches and texture datasets. It begins with an introduction to texture classification and its general framework. Key steps in texture classification are preprocessing, feature extraction, and classification. The document then discusses several common feature extraction methods used in texture classification, including local binary pattern (LBP), scale invariant feature transform (SIFT), speeded up robust features (SURF), Fourier transformation, texture spectrum, and gray level co-occurrence matrix (GLCM). It also reviews three popular classifiers for texture classification: K-nearest neighbors (K-NN), artificial neural network (ANN), and support vector machine (SVM). Finally, it mentions several popular texture datasets that are commonly used for training and testing texture
This document summarizes an evaluation of texture feature extraction methods for content-based image retrieval, including co-occurrence matrices, Tamura features, and Gabor filters. The evaluation tested these methods on a Corel image collection using Manhattan distance as the similarity measure. Co-occurrence matrices performed best with homogeneity as the feature, while Gabor wavelets showed better performance for homogeneous textures of fixed sizes. Tamura features performed poorly with directionality. Overall, co-occurrence matrices provided the best results for general texture retrieval.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
This paper proposes a novel technique for detecting point landmarks in 3D medical images based on phase congruency (PC). A bank of 3D log-Gabor filters is used to compute energy maps from the images. These energy maps are combined to form the PC measure, which is invariant to intensity variations and provides good feature localization. Significant 3D point landmarks are detected by analyzing the eigenvectors of PC moments computed at each point. The method is demonstrated on head and neck images for radiation therapy planning.
IRJET-A Review on Implementation of High Dimension Colour Transform in Domain...IRJET Journal
This document reviews algorithms for detecting salient regions in images using high dimensional color transforms. It summarizes several existing methods that use color contrast, frequency analysis, and superpixel segmentation. A key method discussed creates a saliency map by finding the optimal linear combination of color coefficients in a high dimensional color space. This allows more accurate detection of salient objects versus methods using only RGB color. The performance of this high dimensional color transform method is improved by also utilizing relative location and color contrast between superpixels as learned features.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
An Automatic Color Feature Vector Classification Based on Clustering MethodRSIS International
In computer vision application, visual features such as
shape, color and texture are extracted to characterize images.
Each of the features is represented using one or more feature
descriptors. One of the important requirements in image
retrieval, indexing, classification, clustering, etc. is extracting
efficient features from images. The color feature is one of the
most widely used visual features. Use of color histogram is the
most common way for representing color feature. One of
disadvantage of the color histogram is that it does not take the
color spatial distribution into consideration. In this paper an
automatic color feature vector classification based on clustering
approach is presented, which effectively describes the spatial
information of color features. The image retrieval results are
compare to improved color feature vector show the acceptable
efficiency of this approach. It propose an automatic color feature
vector classification of satellite images using clustering approach.
The intention is to study cluster a set of satellite images in several
categories on the color similarity basis. The images are processed
using LAB color space in the feature extraction stage. The
resulted color-based feature vectors are clustered using an
automatic unsupervised classification algorithm. Some
experiments based on the proposed recognition technique have
also been performed. More research, however, is needed to
identify and reduce uncertainties in the image processing chain
to improve classification accuracy. The mathematical training
and prediction analysis of a general familiarity with satellite
classifications meet typical map accuracy standards.
International Journal of Engineering Research and DevelopmentIJERD Editor
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Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
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Civil and Architecture Engineering,
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Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Color Particle Filter Tracking using Frame Segmentation based on JND Color an...IOSRJVSP
Object tracking is one of the most important components in numerous applications of computer vision. Color can provide an efficient visual feature for tracking non-rigid objects in real-time. The color is chosen as tracking feature to make the process scale and rotation invariant. The color of an object can vary over time due to variations in the illumination conditions, the visual angle and the camera parameters. This paper presents the integration of color distributions into particle filtering. The color feature is extracted using our novel 4D color histogram of the image, which is determined using JND color similarity threshold and connectivity of the neighboring pixels. Particle filter tracks several hypotheses simultaneously and weighs them according to their similarity to the target model. The popular Bhattacharyya coefficient is used as similarity measure between two color distributions. The tracking results are compared on the basis of precision over the data set of video sequences from the website http://visualtracking.net of CVPR13 bench marking paper. The proposed tracker yields better precision values as compared to previous reported results
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Vibration analysis and diagnostics for oil production units by pumping rodeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document summarizes a study on the heat transfer through a journal bearing. It describes the methodology used, which included collecting data on the bearing, performing design calculations, creating a geometric model, and conducting thermal analysis using FEA software. The analysis found that the bearing's temperature ranged from 79.76 to 90.96 degrees C, with most of the surface between 84-88 degrees C. It also determined that up to 14,328 watts of heat was generated within the bearing and up to 1,932 watts of heat was dissipated from the bearing casing through convection.
This document summarizes a research paper that proposes a parallel k-nearest neighbors (kNN) algorithm using OpenCL on a GPU architecture. The key points are:
1) kNN classification is computationally intensive, especially for large datasets, creating a need for parallelization.
2) The authors designed and implemented a parallel kNN algorithm using OpenCL to distribute distance computations across GPU cores.
3) Experimental results on UCI datasets showed the parallel kNN approach improved performance over a serial kNN implementation.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
A comparative study of secure search protocols in pay as-you-go cloudseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Efficient distributed detection of node replication attacks in mobile sensor ...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Thermodynamic behavior of tetrahydrofuron in p dioxane, methylcyclohexane and...eSAT Publishing House
This document summarizes a study on the thermodynamic behavior of tetrahydrofuron liquid mixtures with p-dioxane, methylcyclohexane, and cyclohexanol. The study applies an equation of state model to calculate ultrasonic velocity, density, and other thermodynamic parameters. Close agreement was found between calculated and experimental values, indicating the model provides a good representation of molecular clustering in liquid states. Parameters like minimum potential depth and hard sphere diameter were determined for the pure components and in mixtures.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This document discusses cell search and synchronization procedures in Long Term Evolution (LTE) cellular networks. It describes how a mobile unit detects and locks onto base stations when powering on or moving between cells. The mobile unit first detects the Primary Synchronization Signal (PSS) to synchronize on the subframe boundary and determine the physical layer cell identity. It then detects the Secondary Synchronization Signal (SSS) to obtain the cell identity group number and complete cell ID detection. Simulations are presented showing the probability of detecting neighboring cells under different channel conditions and signal-to-noise ratios, with better detection at cell centers compared to edges.
Production of lactic acid from sweet meat industry waste by lactobacillus del...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Evaluvation of noise level and its adverse effect in metal die manufacuturing...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Critical comparison of ground motion attenuation formulae for recent earthqua...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document presents a methodology for real-time object tracking using a webcam. It combines Prewitt edge detection for object detection and Kalman filtering for tracking. Prewitt edge detection is used to detect the edges of the moving object in each video frame. Then, Kalman filtering is used to track the detected object across subsequent frames by predicting its location. Experiments show the approach can efficiently track objects under deformation, occlusion, and can track multiple objects simultaneously. The combination of Prewitt edge detection and Kalman filtering provides an effective method for real-time object tracking.
Comparative performance analysis of segmentation techniquesIAEME Publication
This document compares the performance of several image segmentation techniques: global thresholding, adaptive thresholding, region growing, and level set segmentation. It applies these techniques to medical and synthetic images corrupted with noise and evaluates the segmentation results using binary classification metrics like sensitivity, specificity, accuracy, and precision. The results show that level set segmentation best preserves object boundaries, adaptive thresholding captures most image details, and global thresholding has the highest success rate at extracting regions of interest. Overall, the study aims to determine the optimal segmentation method for medical images from CT scans.
A NOVEL PROBABILISTIC BASED IMAGE SEGMENTATION MODEL FOR REALTIME HUMAN ACTIV...sipij
Automatic human activity detection is one of the difficult tasks in image segmentation application due to
variations in size, type, shape and location of objects. In the traditional probabilistic graphical
segmentation models, intra and inter region segments may affect the overall segmentation accuracy. Also,
both directed and undirected graphical models such as Markov model, conditional random field have
limitations towards the human activity prediction and heterogeneous relationships. In this paper, we have
studied and proposed a natural solution for automatic human activity segmentation using the enhanced
probabilistic chain graphical model. This system has three main phases, namely activity pre-processing,
iterative threshold based image enhancement and chain graph segmentation algorithm. Experimental
results show that proposed system efficiently detects the human activities at different levels of the action
datasets.
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International Journal of Computational Engineering Research(IJCER) ijceronline
This document presents a hybrid methodology for classifying segmented images using both unsupervised and supervised classification techniques. The proposed methodology involves first segmenting the image into spectrally homogeneous regions using region growing segmentation. Then, a clustering algorithm is applied to the segmented regions for initial classification. Selected regions are used as training data for a supervised classification algorithm to further categorize the image. The hybrid approach combines the benefits of unsupervised clustering and supervised classification. The methodology is evaluated on natural and aerial images to compare its performance to existing seeded region growing and texture extraction segmentation methods.
Object extraction using edge, motion and saliency information from videoseSAT Journals
Abstract Object detection is a process of finding the instances of object of a certain class which is useful in analysis of video or image. There are number of algorithms have been developed so far for object detection. Object detection has got significant role in variety of areas of computer vision like video surveillance, image retrieval`. In this paper presented an efficient algorithm for moving object extraction using edge, motion and saliency information from videos. Out methodology includes 4 stages: Frame generation, Pre-processing, Foreground generation and integration of cues. Foreground generation includes edge detection using sobel edge detection algorithm, motion detection using pixel-based absolute difference algorithm and motion saliency detection. Conditional Random Field (CRF) is applied for integration of cues and thus we get better spatial information of segmented object. Keywords: Object detection, Saliency information, Sobel edge detection, CRF.
Image Segmentation from RGBD Images by 3D Point Cloud Attributes and High-Lev...CSCJournals
The document describes an image segmentation algorithm that uses both color and depth features extracted from RGBD images captured by a Kinect sensor. The algorithm clusters pixels into segments based on their color, texture, 3D spatial coordinates, surface normals, and the output of a graph-based segmentation algorithm. Depth features help resolve illumination issues and occlusion that cannot be handled by color-only methods. The algorithm was tested on commercial building images and showed potential for real-time applications.
Adaptive Image Contrast with Binarization Technique for Degraded Document Imagetheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
An efficient image segmentation approach through enhanced watershed algorithmAlexander Decker
This document proposes an efficient image segmentation approach combining an enhanced watershed algorithm and color histogram analysis. The watershed algorithm is applied to preprocessed images after merging the results with an enhanced edge detection. Over-segmentation issues are addressed through a post-processing step applying color histogram analysis to each segmented region, improving overall performance. The document provides background on image segmentation techniques, reviews related work applying watershed algorithms, and discusses challenges like over-segmentation that watershed approaches can face.
This document provides a survey of various image segmentation techniques used in image processing. It begins with an introduction to image segmentation and its importance in fields like pattern recognition and medical imaging. It then categorizes and describes different segmentation approaches like edge-based, threshold-based, region-based, etc. The literature survey section summarizes several papers on specific segmentation algorithms or applications. It concludes with a table comparing the advantages and disadvantages of different segmentation techniques. The overall document aims to provide an overview of segmentation methods and their uses in computer vision.
A Survey on Image Segmentation and its Applications in Image Processing IJEEE
As technology grows day by day computer vision becomes a vital field of understanding the behavior of an image. Image segmentation is a sub field of computer vision that deals with the partition of objects into number of segments. Image segmentation found a huge application in pattern reorganization, texture analysis as well as in medial image processing. This paper focus on distinct sort of image segmentation techniques that are utilized in computer vision. Thus a survey has been created for various image segmentation techniques that describe the importance of the same. Comparison and conclusion has been created within the finish of this paper.
Review of Image Segmentation Techniques based on Region Merging ApproachEditor IJMTER
Image segmentation is an important task in computer vision and object recognition. Since
fully automatic image segmentation is usually very hard for natural images, interactive schemes with a
few simple user inputs are good solutions. In image segmentation the image is dividing into various
segments for processing images. The complexity of image content is a bigger challenge for carrying out
automatic image segmentation. On regions based scheme, the images are merged based on the similarity
criteria depending upon comparing the mean values of both the regions to be merged. So, the similar
regions are then merged and the dissimilar regions are merged together.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity
Abstract Edge detection is a fundamental tool used in most image processing applications. We proposed a simple, fast and efficient technique to detect the edge for the identifying, locating sharp discontinuities in an image and boundary of an image. In this paper, we found that proposed method called LookUp Table performs well, which requires least computational time as compared to conventional Edge Detection techniques. And also in this paper we presented a comparative performance of various conventional Edge Detection Techniques. Keywords: Edge detectors, Lookup table.
Image fusion using nsct denoising and target extraction for visual surveillanceeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Analysis and Comparison of various Methods for Text Detection from Images usi...rahulmonikasharma
In this paper analysis and comparison of various methods for text detection is carried by using canny edge detection algorithm and MSER based method along with the image enhancement which results in the improved performance in terms of text detection. In addition, we improve current MSERs by developing a contrast enhancement mechanism that enhances region stability of text patterns to remove the blurring caused during the capture of image Lucy Richardson de blurring Algorithm is used.
Multitude Regional Texture Extraction for Efficient Medical Image Segmentationinventionjournals
Image processing plays a major role in evaluation of images in many concerns. Manual interpretation of the image is time consuming process and it is susceptible to human errors. Computer assisted approaches for analyzing the images have increased in latest evolution of image processing. Also it has highlighted its performance more in the field of medical sciences. Many techniques are available for the involvement in processing of images, evaluation, extraction etc. The main goal of image segmentation is cluster pixeling the regions corresponding to individual surfaces, objects, or natural parts of objects and to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. The proposed method is to conquer segmentation and texture extraction with Regional and Multitude and techniques involved in it. Ultrasound (US) is increasingly considered as a viable alternative imaging modality in computer-assisted brain segmentation and disease diagnosis applications.First for ultra sound we present region based segmentation.Homogeneous regions depends on image granularity features. Second a local threshold based multitude texture regional seed segmentation for medical image segmentation is proposed. Here extraction is done with dimensions comparable to the speckle size are to be extracted. The algorithm provides a less medical metrics awareness in a minimum user interaction environment. The shape and size of the growing regions depend on look up table entries.
This document discusses techniques for image segmentation and edge detection. It proposes a generalized boundary detection method called Gb that combines low-level and mid-level image representations in a single eigenvalue problem to detect boundaries. Gb achieves state-of-the-art results at low computational cost. Soft segmentation is also introduced to improve boundary detection accuracy with minimal extra computation. Common methods for edge detection are described, including gradient-based, texture-based, and projection profile-based approaches. Improved Harris and corner detection algorithms are presented to more accurately detect edges and corners. The output of Gb using soft segmentations as input is shown to correlate well with occlusions and whole object boundaries while capturing general boundaries.
Performance of Efficient Closed-Form Solution to Comprehensive Frontier Exposureiosrjce
This document discusses boundary detection techniques for images. It proposes a generalized boundary detection method (Gb) that combines low-level and mid-level image representations in a single eigenvalue problem to detect boundaries. Gb achieves state-of-the-art results at low computational cost. Soft segmentation and contour grouping methods are also introduced to further improve boundary detection accuracy with minimal extra computation. The document presents outputs of Gb on sample images and concludes that Gb effectively detects boundaries in a principled manner by jointly resolving constraints from multiple image interpretation layers in closed form.
REGION CLASSIFICATION AND CHANGE DETECTION USING LANSAT-8 IMAGESADEIJ Journal
The change detection in remote sensing images remains an important and open problem for damage assessment. A new change detection method for LANSAT-8 images based on homogeneous pixel transformation (HPT) is proposed. Homogeneous Pixel Transformation transfers one image from its original feature space (e.g., gray space) to another feature space (e.g., spectral space) in pixel-level to make the pre-event images and post-event images to be represented in a common space or projection space for the convenience of change detection. HPT consists of two operations, i.e., forward transformation and backward transformation. In the forward transformation, each pixel of pre-event image in the first feature space is taken and will estimate its mapping pixel in the second space corresponding to post-event image based on the known unchanged pixels. A multi-value estimation method with the noise tolerance is produced to determine the mapping pixel using K-nearest neighbours technique. Once the mapping pixels of pre-event image are identified, the difference values between the mapping image and the post-event image can be directly generated. Then the similar work is done for backward transformation to combine the post-event image with the first space, and one more difference value for each pixel will be generated. Then, the two difference values are taken and combined to improve the robustness of detection with respect to the noise and heterogeneousness of images. (FRFCM) Fast and Robust Fuzzy C-means clustering algorithm is employed to divide the integrated difference values into two clusters- changed pixels and unchanged pixels. This detection results may contain few noisy regions as small error detections, and a spatial-neighbor based noise filter is developed to reduce the false alarms and missing detections. The experiments for change detection with real images of LANSAT-8 in Tuticorin between 2013-2019 are given to validate the percentage of the changed regions in the proposed method.
Similar to A novel predicate for active region merging in automatic image segmentation (20)
Hudhud cyclone caused extensive damage in Visakhapatnam, India in October 2014, especially to tree cover. This will likely impact the local environment in several ways: increased air pollution as trees absorb less; higher temperatures without tree canopy; increased erosion and landslides. It also created large amounts of waste from destroyed trees. Proper management of solid waste is needed to prevent disease spread. Suggested measures include restoring damaged plants, building fountains to reduce heat, mandating light-colored buildings, improving waste management, and educating public on health risks. Overall, changes are needed to water, land, and waste practices to rebuild the environment after the cyclone removed green cover.
Impact of flood disaster in a drought prone area – case study of alampur vill...eSAT Publishing House
1) In September-October 2009, unprecedented heavy rainfall and dam releases caused widespread flooding in Alampur village in Mahabub Nagar district, a historically drought-prone area.
2) The flood damaged or destroyed homes, buildings, infrastructure, crops, and documents. It displaced many residents and cut off the village.
3) The socioeconomic conditions and mud-based construction of homes in the village exacerbated the flood's impacts, making damage more severe and recovery more difficult.
The document summarizes the Hudhud cyclone that struck Visakhapatnam, India in October 2014. It describes the cyclone's formation, rapid intensification to winds of 175 km/h, and landfall near Visakhapatnam. The cyclone caused extensive damage estimated at over $1 billion and at least 109 deaths in India and Nepal. Infrastructure like buildings, bridges, and power lines were destroyed. Crops and fishing boats were also damaged. The document then discusses coping strategies and improvements needed to disaster management plans to better prepare for future cyclones.
Groundwater investigation using geophysical methods a case study of pydibhim...eSAT Publishing House
This document summarizes the results of a geophysical investigation using vertical electrical sounding (VES) methods at 13 locations around an industrial area in India. The VES data was interpreted to generate geo-electric sections and pseudo-sections showing subsurface resistivity variations. Three main layers were typically identified - a high resistivity topsoil, a weathered middle layer, and a basement rock. Pseudo-sections revealed relatively more weathered areas in the northwest and southwest. Resistivity sections helped identify zones of possible high groundwater potential based on low resistivity anomalies sandwiched between more resistive layers. The study concluded the electrical resistivity method was useful for understanding subsurface geology and identifying areas prospective for groundwater exploration.
Flood related disasters concerned to urban flooding in bangalore, indiaeSAT Publishing House
1. The document discusses urban flooding in Bangalore, India. It describes how factors like heavy rainfall, population growth, and improper land use have contributed to increased flooding in the city.
2. Flooding events in 2013 are analyzed in detail. A November rainfall caused runoff six times higher than the drainage capacity, inundating low-lying residential areas.
3. Impacts of urban flooding include disrupted daily life, damaged infrastructure, and decreased economic activity in affected areas. The document calls for improved flood management strategies to better mitigate urban flooding risks in Bangalore.
Enhancing post disaster recovery by optimal infrastructure capacity buildingeSAT Publishing House
This document discusses enhancing post-disaster recovery through optimal infrastructure capacity building. It presents a model to minimize the cost of meeting demand using auxiliary capacities when disaster damages infrastructure. The model uses genetic algorithms to select optimal capacity combinations. The document reviews how infrastructure provides vital services supporting recovery activities and discusses classifying infrastructure into six types. When disaster reduces infrastructure services, a gap forms between community demands and available support, hindering recovery. The proposed research aims to identify this gap and optimize capacity selection to fill it cost-effectively.
Effect of lintel and lintel band on the global performance of reinforced conc...eSAT Publishing House
This document analyzes the effect of lintels and lintel bands on the seismic performance of reinforced concrete masonry infilled frames through non-linear static pushover analysis. Four frame models are considered: a frame with a full masonry infill wall; a frame with a central opening but no lintel/band; a frame with a lintel above the opening; and a frame with a lintel band above the opening. The results show that the full infill wall model has 27% higher stiffness and 32% higher strength than the model with just an opening. Models with lintels or lintel bands have slightly higher strength and stiffness than the model with just an opening. The document concludes lintels and lintel
Wind damage to trees in the gitam university campus at visakhapatnam by cyclo...eSAT Publishing House
1) A cyclone with wind speeds of 175-200 kph caused massive damage to the green cover of Gitam University campus in Visakhapatnam, India. Thousands of trees were uprooted or damaged.
2) A study assessed different types of damage to trees from the cyclone, including defoliation, salt spray damage, damage to stems/branches, and uprooting. Certain tree species were more vulnerable than others.
3) The results of the study can help in selecting more wind-resistant tree species for future planting and reducing damage from future storms.
Wind damage to buildings, infrastrucuture and landscape elements along the be...eSAT Publishing House
1) A visual study was conducted to assess wind damage from Cyclone Hudhud along the 27km Visakha-Bheemli Beach road in Visakhapatnam, India.
2) Residential and commercial buildings suffered extensive roof damage, while glass facades on hotels and restaurants were shattered. Infrastructure like electricity poles and bus shelters were destroyed.
3) Landscape elements faced damage, including collapsed trees that damaged pavements, and debris in parks. The cyclone wiped out over half the city's green cover and caused beach erosion around protected areas.
1) The document reviews factors that influence the shear strength of reinforced concrete deep beams, including compressive strength of concrete, percentage of tension reinforcement, vertical and horizontal web reinforcement, aggregate interlock, shear span-to-depth ratio, loading distribution, side cover, and beam depth.
2) It finds that compressive strength of concrete, tension reinforcement percentage, and web reinforcement all increase shear strength, while shear strength decreases as shear span-to-depth ratio increases.
3) The distribution and amount of vertical and horizontal web reinforcement also affects shear strength, but closely spaced stirrups do not necessarily enhance capacity or performance.
Role of voluntary teams of professional engineers in dissater management – ex...eSAT Publishing House
1) A team of 17 professional engineers from various disciplines called the "Griha Seva" team volunteered after the 2001 Gujarat earthquake to provide technical assistance.
2) The team conducted site visits, assessments, testing and recommended retrofitting strategies for damaged structures in Bhuj and Ahmedabad. They were able to fully assess and retrofit 20 buildings in Ahmedabad.
3) Factors observed that exacerbated the earthquake's impacts included unplanned construction, non-engineered buildings, improper prior retrofitting, and defective materials and workmanship. The professional engineers' technical expertise was crucial for effective post-disaster management.
This document discusses risk analysis and environmental hazard management. It begins by defining risk, hazard, and toxicity. It then outlines the steps involved in hazard identification, including HAZID, HAZOP, and HAZAN. The document presents a case study of a hypothetical gas collecting station, identifying potential accidents and hazards. It discusses quantitative and qualitative approaches to risk analysis, including calculating a fire and explosion index. The document concludes by discussing hazard management strategies like preventative measures, control measures, fire protection, relief operations, and the importance of training personnel on safety.
Review study on performance of seismically tested repaired shear wallseSAT Publishing House
This document summarizes research on the performance of reinforced concrete shear walls that have been repaired after damage. It begins with an introduction to shear walls and their failure modes. The literature review then discusses the behavior of original shear walls as well as different repair techniques tested by other researchers, including conventional repair with new concrete, jacketing with steel plates or concrete, and use of fiber reinforced polymers. The document focuses on evaluating the strength retention of shear walls after being repaired with various methods.
Monitoring and assessment of air quality with reference to dust particles (pm...eSAT Publishing House
This document summarizes a study on monitoring and assessing air quality with respect to dust particles (PM10 and PM2.5) in the urban environment of Visakhapatnam, India. Sampling was conducted in residential, commercial, and industrial areas from October 2013 to August 2014. The average PM2.5 and PM10 concentrations were within limits in residential areas but moderate to high in commercial and industrial areas. Exceedance factor levels indicated moderate pollution for residential areas and moderate to high pollution for commercial and industrial areas. There is a need for management measures like improved public transport and green spaces to combat particulate air pollution in the study areas.
Low cost wireless sensor networks and smartphone applications for disaster ma...eSAT Publishing House
This document describes a low-cost wireless sensor network and smartphone application system for disaster management. The system uses an Arduino-based wireless sensor network comprising nodes with various sensors to monitor the environment. The sensor data is transmitted to a central gateway and then to the cloud for analysis. A smartphone app connected to the cloud can detect disasters from the sensor data and send real-time alerts to users to help with early evacuation. The system aims to provide low-cost localized disaster detection and warnings to improve safety.
Coastal zones – seismic vulnerability an analysis from east coast of indiaeSAT Publishing House
This document summarizes an analysis of seismic vulnerability along the east coast of India. It discusses the geotectonic setting of the region as a passive continental margin and reports some moderate seismic activity from offshore in recent decades. While seismic stability cannot be assumed given events like the 2004 tsunami, no major earthquakes have been recorded along this coast historically. The document calls for further study of active faults, neotectonics, and implementation of improved seismic building codes to mitigate vulnerability.
Can fracture mechanics predict damage due disaster of structureseSAT Publishing House
This document discusses how fracture mechanics can be used to better predict damage and failure of structures. It notes that current design codes are based on small-scale laboratory tests and do not account for size effects, which can lead to more brittle failures in larger structures. The document outlines how fracture mechanics considers factors like size effect, ductility, and minimum reinforcement that influence the strength and failure behavior of structures. It provides examples of how fracture mechanics has been applied to problems like evaluating shear strength in deep beams and investigating a failure of an oil platform structure. The document argues that fracture mechanics provides a more scientific basis for structural design compared to existing empirical code provisions.
This document discusses the assessment of seismic susceptibility of reinforced concrete (RC) buildings. It begins with an introduction to earthquakes and the importance of vulnerability assessment in mitigating earthquake risks and losses. It then describes modeling the nonlinear behavior of RC building elements and performing pushover analysis to evaluate building performance. The document outlines modeling RC frames and developing moment-curvature relationships. It also summarizes the results of pushover analyses on sample 2D and 3D RC frames with and without shear walls. The conclusions emphasize that pushover analysis effectively assesses building properties but has limitations, and that capacity spectrum method provides appropriate results for evaluating building response and retrofitting impact.
A geophysical insight of earthquake occurred on 21 st may 2014 off paradip, b...eSAT Publishing House
1) A 6.0 magnitude earthquake occurred off the coast of Paradip, Odisha in the Bay of Bengal on May 21, 2014 at a depth of around 40 km.
2) Analysis of magnetic and bathymetric data from the area revealed the presence of major lineaments in NW-SE and NE-SW directions that may be responsible for seismic activity through stress release.
3) Movements along growth faults at the margins of large Bengal channels, due to large sediment loads, could also contribute to seismic events by triggering movements along the faults.
Effect of hudhud cyclone on the development of visakhapatnam as smart and gre...eSAT Publishing House
This document discusses the effects of Cyclone Hudhud on the development of Visakhapatnam as a smart and green city through a case study and preliminary surveys. The surveys found that 31% of participants had experienced cyclones, 9% floods, and 59% landslides previously in Visakhapatnam. Awareness of disaster alarming systems increased from 14% before the 2004 tsunami to 85% during Cyclone Hudhud, while awareness of disaster management systems increased from 50% before the tsunami to 94% during Hudhud. The surveys indicate that initiatives after the tsunami improved awareness and preparedness. Developing Visakhapatnam as a smart, green city should consider governance
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
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- Basic understanding of AWS services and architecture
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- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
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- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
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- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
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- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
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Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
AI for Legal Research with applications, toolsmahaffeycheryld
AI applications in legal research include rapid document analysis, case law review, and statute interpretation. AI-powered tools can sift through vast legal databases to find relevant precedents and citations, enhancing research accuracy and speed. They assist in legal writing by drafting and proofreading documents. Predictive analytics help foresee case outcomes based on historical data, aiding in strategic decision-making. AI also automates routine tasks like contract review and due diligence, freeing up lawyers to focus on complex legal issues. These applications make legal research more efficient, cost-effective, and accessible.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Mechanical Engineering on AAI Summer Training Report-003.pdf
A novel predicate for active region merging in automatic image segmentation
1. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 542
A NOVEL PREDICATE FOR ACTIVE REGION MERGING IN
AUTOMATIC IMAGE SEGMENTATION
S.Muthamizhselvi1
, D.Jeyakumari2
, R.Kannan3
1
PG Scholar, 2
Associate Professor, 3
Assistant Professor,
1, 2, 3
Department of ECE, RVS college of Engineering and Technology, Coimbatore, Tamilnadu, India
muthamizhselvi24@gmail.com, dgjeyakumari@gmail.com, kannanvlsi@gmail.com
Abstract
Image segmentation is an elementary task in computer vision and image processing. This paper deals with the automatic image
segmentation in a region merging method. Two essential problems in a region merging algorithm: order of merging and the stopping
criterion. These two problems are solved by a novel predicate which is described by the sequential probability ratio test and the
minimal cost criterion. In this paper we propose an Active Region merging algorithm which utilizes the information acquired from
perceiving edges in color images in L*a*b* color space. By means of color gradient recognition method, pixels with no edges are
clustered and considered alone to recognize some preliminary portion of the input image. The color information along with a region
growth map consisting of completely grown regions are used to perform an Active region merging method to combine regions with
similar characteristics. Experiments on real natural images are performed to demonstrate the performance of the proposed Active
region merging method.
Index Terms: Adaptive threshold generation, CIE L*a*b* color gradient, region merging, Sequential Probability Ratio
Test (SPRT).
-----------------------------------------------------------------------***-----------------------------------------------------------------------
1. INTRODUCTION:
For some applications such as image recognition (or) image
compression, we cannot process the whole image directly for
the reason as it is inefficient and impractical. Therefore we are
going for image segmentation before recognition (or)
compression. Image segmentation is a basic yet still a
demanding problem in computer vision and image processing.
Image segmentation is a key process in object recognition,
target tracking, content-based image retrieval, and medical
image processing, video, and computer vision applications like
medical image analysis such as locating tumors and other
pathologies, in locating objects in satellite images, in face
recognition, fingerprint recognition etc. The goal of image
segmentation is to partition an image into a certain number of
pieces that have coherent features (color, texture, etc.) and, in
the meanwhile, to group the meaningful pieces together for the
convenience of perceiving. In many practical applications, as a
large number of images are needed to be handled, human
interactions involved in the segmentation process should be as
less as possible. For this several general-purpose algorithms
and techniques have been developed for image segmentation.
There is a large amount of literature on automatic image
segmentation. For Example, the spatiotemporal segmentation
is to identify the objects present in the scene represented in a
video sequence. This technique processes two consecutive
frames at a time. Regions are merged based on their mutual
spatiotemporal similarity. Modified Kolmogorov -Smirnov
test for estimating the temporal similarity. This test efficiently
uses temporal information in both the residual distribution and
the motion parametric representation. There are two
complementary graph-based clustering rules are proposed,
namely, the strong rule and the weak rule. The weak rule is
applied after the strong rule. It cannot combine the tracking
information into the segmentation process. The objects
forming the scene are not tracked through time [8]. A hybrid
multidimensional image segmentation algorithm, which
combines edge and region-based techniques through the
morphological algorithm of watersheds. An edge-preserving
statistical noise reduction approach is used as a preprocessing
stage in order to compute an accurate estimate of the image
gradient. Then, an initial partitioning of the image into
primitive regions is produced by applying the watershed
transform on the image gradient magnitude. This initial
segmentation is the input to a computationally efficient
hierarchical region merging process that produces the final
segmentation. The latter process uses the region adjacency
graph (RAG) and nearest neighbor graph (NNG)
representation of the image regions. The final segmentation
provides, due to the RAG, one-pixel wide, closed, and
accurately localized contours/surfaces. It does not involve in
the segmentation of moving 3D images [13].
Different algorithms, based on a combination of two structures
of graph and of two color image processing methods, in order
2. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 543
to segment color images. The structures used in this study are
the region adjacency graph and the line graph associated. It
shows how these structures can enhance segmentation
processes such as region growing or watershed transformation.
The principal advantage of these structures is that they give
more weight to adjacency relationships between regions than
usual methods [1]. Many tasks in computer vision involve
assigning a label (such as disparity) to every pixel. A common
constraint is that the labels should vary smoothly almost
everywhere while preserving sharp discontinuities that may
exist, e.g., at object boundaries. These tasks are naturally
stated in terms of energy minimization. In this paper, we
consider a wide class of energies with various smoothness
constraints. Global minimization of these energy functions is
NP-hard even in the simplest discontinuity-preserving case.
Two algorithms based on graph cuts that efficiently find a
local minimum with respect to two types of large moves,
namely expansion moves and swap moves. These moves can
simultaneously change the labels of arbitrarily large sets of
pixels. It can find only a local minimum [2].
A database containing „ground truth‟ segmentations produced
by humans for images of a wide variety of natural scenes.
They define an error measure which quantifies the consistency
between segmentations of differing granularities and find that
different human segmentations of the same image are highly
consistent. Use of this dataset is demonstrated in two
applications: (1) evaluating the performance of segmentation
algorithms and (2) measuring probability distributions
associated with Gestalt grouping factors as well as statistics of
image region properties [6]. The technique of scale
multiplication is analyzed in the framework of canny edge
detection. A scale multiplication function is defined as the
product of the responses of the detection filter at two scales.
Edge maps are constructed as the local maxima by
thresholding the scale multiplication results. The detection and
localization criteria of the scale multiplication are derived. At
a small loss in the detection criterion, the localization criterion
can be much improved by scale multiplication. The product of
the two criteria for scale multiplication is greater than that for
a single scale, which leads to better edge detection
performance. [13]
A current level set image segmentation methods, the number
of regions assumed to be known beforehand. As a result, it
remains constant during the optimization of the objective
functional. This study investigates a region merging prior
related to regions area to allow the number of regions to vary
automatically during curve evolution, thereby optimizing the
objective functional implicitly with respect to the number of
regions. The paper gives a statistical interpretation to the
coefficient of this prior to balance its effect systematically
against the other functional terms. They demonstrate the
validity and efficiency of the method by testing on real images
of intensity, color, and motion [4]. The GSEG algorithm is
primarily based on edge detection, dynamic region growth and
multi-resolution region merging [19].
2. PROPOSED METHOD:
The proposed algorithm consists of three steps. First, an edge
detection algorithm is used to produce an edge-map used in
the creation of adaptive gradient thresholds, which selects the
regions of nearby pixels that display similar gradient and color
values, producing an initial segmentation map. Second, a
region growing algorithm is used for growing the regions.
Finally, an active region merging algorithm is used for
merging the similar regions by using a novel predicate P.
Fig -1: Block diagram of the proposed algorithm
2.1 Edge Detection:
The perceived areas with no edges inside them are the
preliminary clusters or seeds selected to initiate the
segmentation of the image. Assuming that an image is a
function f(x, y), the gradient can be defined as its initial
derivative yfxff ; . For a vector field f, the
gradient vector to be,
xx
xx
xD
fDfD
fDfD
mnm
n
....................
...................
1
111
(1)
where Djfk is the first partial derivative of the kth component
of f with respect to the jth component of x. For a three-
channel color image, the gradient can be calculated as: let
a,b,c denotes each color channel and x,y denote the spatial
coordinates for a pixel. It is expressed as:
Input image
Color space conversion
Adaptive Threshold Generation
Region Growing
Active Region Merged
image
3. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 544
222
dx
dc
dx
db
dx
da
u
(2)
dy
dc
dx
dc
dy
db
dx
db
dy
da
dx
da
v
(3)
222
dy
dc
dy
db
dy
da
w
(4)
2.2 Adaptive Threshold Generation:
The Active Region Merging algorithm is started with a color
space conversion of the input image from RGB to CIE
L*A*B. The magnitude of the gradient G(i,j) of the color
image can be calculated by using L*A*B. Primarily, the aim is
to choose a threshold for the initiation of the seed generation
procedure. Preferably, a threshold value could be choosing to
offer the most edges, where as ignoring the noise in images. A
single threshold that may accurately define the boundary of a
given region can permit the other regions to merge wrongly.
So, we are choosing two initial threshold values for the low
and high gradient content in the image. The high initial
threshold can be used for images which have a large gradient
values over a narrow range and a low initial threshold value
can be used for images which have a large gradient values
over a wide range. It guarantees that all significant low
gradient regions are obtained as initial seeds. Low initial
threshold is denoted as λ and high initial threshold is denoted
as λ+5.
Fig -2: Adaptive Threshold Generation
2.3 Seed Generation:
Preliminary seeds are generated by perceiving all the regions
in the image whose gradient values fall below the initial
thresholds λ, and λ+5. If no regions present under this
threshold, the edge value is increased until regions are
identified. The Preliminary Seed Generation makes use of
individual size necessity to select the preliminary seeds, so as
to prevent numerous seed generation within identical and
associated regions. The initial condition is to implement that
seeds to be superior to 0.5% of the image when looking for
regions with a threshold value lower than λ .The basis of this
rule is that frequently backgrounds have false edges produced
by illumination or other varying factors in this gradient range.
The second condition is to implement that seeds to be superior
to 0.25% of the image in the range λ to λ+5, since it is
necessary to differentiate the regions. For distinguishing
purposes the pixels creating each seed obtain an exclusive
label, the mutual set of labeled seeds is called as the Parent
Seeds (PS).
2.4 Region Growing:
The Parent Seeds (PS) grows by increasing the threshold a
single component at a time, for example from 20 to 21. After
each growth, recognition of new regions or child seeds that
falls below the new threshold happens. These child seeds
requires to be categorized in to adjacent-to-existent or non
adjacent seeds. The non adjacent seeds are surplus, because
they can only be added at the starting of an each adaptive
threshold stage. In order to make the region growth method
capable, it is necessary to recognize the parent seed to which
the child is adjacent. The goal is to process all adjacent child
seeds in a vectorized method. To attain this task, we go on to
perceive the outside edges of the map using a nonlinear spatial
filter. The filter is defined as follows:
Otherwise
jiPSif
jiPSif
jiF ji
,1
0),(,0
0),(,0
),( ,
(5)
where β is the neighborhood. The result of pertaining this filter
creates the boundary of the PS map. Assign the label for each
pixel in the image. Finally, it produces the region growth map.
2.5 Region Merging:
Region merging is the process of merging the two similar
regions. Similarity is based on color, texture, grey level etc.
Region merging operations eliminates false boundaries and
spurious regions by merging adjacent regions that belongs to
the same object. It controls the over segmentation problem.
Here, the Active Region Merging process occurs by using a
region merging predicate P and cue consistency.
2.5.1 Region Merging Predicate:
The proposed predicate is based on measuring the similarity
between the pixels along the boundary of two regions. The
similarity between the two regions R1 and R2 can be
calculated by using an equation given below:
4. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 545
nnRR jiwS ,min, 21
(6)
where ni and nj are the set of nodes corresponding to the
regions, ni belongs to R1 and nj belongs to R2 and (ni,nj)
belongs to edge E. An edge has a corresponding weight w. We
obtain the similarity between the two neighboring regions by
using a minimal weight edge connecting them. The merging
predicate P will decide whether there is an indication of
merging between the two regions. It requires two features: a
similarity measure, which is used to find out the candidate
region for merging and the consistency property, which
verifies if the regions are homogenous. Merge R1 and R2 if
and only if they are the most similar neighbors.
otherwisefalse
consistentareandb
andSSSaiftrue
P
RR
RRRRRR
RR
ba
.
;,min,min
21
212,1
2,1
(7)
where Ra and Rb is the neighboring region of R1 and R2.
Condition (a) indicates that the connecting edge between R1
and R2 to be the minimal one in either of the neighborhood.
Condition (b) acts as a stopping criterion.
2.5.2 Cue Consistency:
In order to attain the similar regions in region merging, the
proposed predicate P verifies the consistency of the regions.
The region information is obtained by the cues. The selection
of cues can be intensity, color, texture and so on. The
spreading of cues depends on the consistency of the pair of
neighboring regions. In this paper, we are going to use a
sequential probability ratio test method. Assuming that
parameter ϕ is connected to the dissemination of random cues
y. There are two premises involved here: a couple of regions is
“consistent” and “inconsistent”. The consistent premises is
denoted as H0 : ϕ=ϕ0 and inconsistent premises is denoted as
H1 : ϕ=ϕ1. The application of the SPRT to the consistency test
of cues is expressed as follows. The sequence of following
likelihood ratio δj is
nj
yP
yP
j
j
j ........,2,1,log
11
00
(8)
where P0(yj/ϕ0) and P1(yj/ϕ1) are the disseminations of cues.
We are going to use the Gaussian distribution model to fairly
accurate the cue distributions. The two conditional
probabilities are expressed as:
KKXK aKbP
KKXK baKbP
abK
T
babK
T
y
y
1
211
1
100
exp
exp
1
(9)
where Ka and Kb are the standard color of sampled data in
regions a and b, and Ka+b is the standard value of the samples
union. Xk is the covariance matrix of the regions and λ1 and
λ2 are the scalar parameters. The arrangement of likelihood
ratio is the addition of individual δj, i.e.,
N
j j1
(10)
where N is the first integer. By using SPRT method, we can
execute the test with a realistic estimation. It can be expressed
as C= log (1-β)/α and D= log β(1-α), where α and β are the
probabilities of decision error given by,
α= Pt {Rejecting H1 when H1 is true}
β= Pt {Accepting H1 when H0 is true}
The selection of α and β gives the region merging feature. α
and β are set to a permanent value of 0.05.
2.5.3 Active Region Merging Algorithm (ARM):
The proposed ARM method deals with the region merging
predicate P. By taking the region merging as an important
problem, the aim is to assign each region a label, such that the
region that belongs to the same object will have the same
label. There are two types of labels for regions: initial label
and final label. The test of consistency and inconsistency is
based on the error probabilities of cue decisions α and β. The
error probabilities are used for finding the homogenous
regions. If any non homogenous regions found, the more
number of tests are used for the decisions. The regions are
arranged in a sequential order from initial label to final label.
It depends on the minimum weight between the two regions.
The whole image is the union of all the regions, F is the sum
of transition costs of overall regions.
R
F
j
jF
(11)
where Fj is the addition of transition costs of Rj.
(a) (b)
5. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 546
(c) (d)
(e)
Fig-3 (a) Input image (b) Color space conversion (c) Gradient
image (d) Region Growing (e) Region Merging.
3. RESULTS AND DISCUSSIONS:
3.1 Choices for Parameters:
In the proposed ARM method, there are five parameters. They
are q, α, β, λ1, λ2 that controls the consistency premises
evaluation.
Here, q is used to select the amount of data for the random
test. α and β are used for the probability of accepting the
consistency and inconsistency and for rejecting the
consistency and inconsistency. In our method, α and β are set
to a constant value of 0.05 and λ1 ranges from 0.01 to 0.05
and λ2 =1.
3.2 Performance Evaluation:
In our method, we are calculating the accuracy for region
growing and Active region merging. The Accuracy can be
expressed as
%100
N
TNTP
(%)Accuracy
The terms used to measure the test performance are true
positive (TP), true negative (TN) and total number of images
(N). Results obtained for each test images are given in Table I.
3.3 Comparison of proposed method with GSEG
algorithm:
Here we are going to compare the segmentation results of
ARM with GSEG algorithm. GSEG performs the
segmentation process by using texture model, color edge
detection and cluster formations. There are two parameters
used here. They are texture channel bandwidth and spatial
bandwidth. The segmented image is based on the texture. The
proposed method contains five parameters q, α, β, λ1, λ2.
Compared to GSEG algorithm, the proposed method produces
good localization of boundaries. It reduces the misclassified
regions and other irregularities of the gradient.
Table -1: Region Merging Accuracy by GSEG and ARM for
various images
(a)
(b) (c)
Fig-4 (a) Input image (b) GSEG image (c) ARM image
CONCLUSIONS
In this paper, we proposed a novel predicate for merging the
regions in automatic image segmentation. The Predicate P is
used to determine the evidence of merging between the two
neighboring regions. The Predicate is defined by using
Sequential Probability Ratio Test (SPRT). It produces the high
efficiency and accuracy. It also reduces the misclassified
edges and boundaries.
Image name Region
Growing
Accuracy
(%)
Region
Merging
Accuracy by
GSEG (%)
Region
Merging
Accuracy by
ARM (%)
Tree 85 87 89
Church 93 95 98
Flowers 82 84 88
Man 80 83 85
6. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 547
ACKNOWLEDGEMENTS
The authors would like to thank their colleagues for their
valuable reviews and comments.
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BIOGRAPHIES:
S.Muthamizhselvi received the B.E.
degree in Electronics and communication
engineering from Sree Sowdambika
college of Engineering under Anna
University, Tirunelveli, Tamil Nadu,
India in 2011 and doing M.E. degree in
Communication Systems from RVS
College of Engineering and Technology,
Coimbatore, Tamil Nadu, India. She has presented papers in
the national and International conferences.
D.Jeyakumari received the B.E. degree
in Electronics and communication
engineering from Madurai Kamaraj
University, Madurai, Tamil Nadu, India
in 1997 and M.E. degree in Applied
Electronics from Government College of
Technology, Coimbatore, Tamil Nadu,
and India in 2005. She is doing her Ph.D.
Programme in Anna University, Coimbatore. She has 16 years
of teaching experience. She has published 5 papers in the
reputed international journals and 20 papers in the national
and international conferences. Presently working as an
Associate Professor in ECE Department at RVS College
Engineering and Technology, Coimbatore. She is a life
member of ISTE.
7. IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163
__________________________________________________________________________________________
Volume: 02 Issue: 04 | Apr-2013, Available @ http://www.ijret.org 548
R.Kannan received the B.E. degree in
Electronics and communication
engineering from Dr.Sivanti Adithanar
college of Engineering, Tiruchendur,
Tamil Nadu, India in 2004 and M.E.
degree in VLSI Design from Sona
College of Technology, Salem, Tamil
Nadu, and India in 2007. He has 7
years of teaching experience. He has
presented papers in the national and international conferences.
Presently working as an Assistant Professor in ECE
Department at RVS College Engineering and Technology,
Coimbatore.