Content-based image retrieval (CBIR) is a method of
finding images from a huge image database according to persons’
interests. Content-based here means that the search involves
analysis the actual content present in the image. As database of
images is growing daybyday, researchers/scholars are searching
for better techniques for retrieval of images maintaining good
efficiency. This paper presents the visual features and various
ways for image retrieval from the huge image database.
MMFO: modified moth flame optimization algorithm for region based RGB color i...IJECEIAES
Region-based color image segmentation is elementary steps in image processing and computer vision. The region-based color image segmentation has faced the problem of multidimensionality. The color image is considered in five-dimensional problems, in which three dimensions in color (RGB) and two dimensions in geometry (luminosity layer and chromaticity layer). In this paper, L*a*b color space conversion has been used to reduce the one dimension and geometrically it converts in the array hence the further one dimension has been reduced. This paper introduced, an improved algorithm modified moth flame optimization (MMFO) algorithm for RGB color image segmentation which is based on bio-inspired techniques. The simulation results of MMFO for region based color image segmentation are performed better as compared to PSO and GA, in terms of computation times for all the images. The experiment results of this method gives clear segments based on the different color and the different number of clusters is used during the segmentation process.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
MMFO: modified moth flame optimization algorithm for region based RGB color i...IJECEIAES
Region-based color image segmentation is elementary steps in image processing and computer vision. The region-based color image segmentation has faced the problem of multidimensionality. The color image is considered in five-dimensional problems, in which three dimensions in color (RGB) and two dimensions in geometry (luminosity layer and chromaticity layer). In this paper, L*a*b color space conversion has been used to reduce the one dimension and geometrically it converts in the array hence the further one dimension has been reduced. This paper introduced, an improved algorithm modified moth flame optimization (MMFO) algorithm for RGB color image segmentation which is based on bio-inspired techniques. The simulation results of MMFO for region based color image segmentation are performed better as compared to PSO and GA, in terms of computation times for all the images. The experiment results of this method gives clear segments based on the different color and the different number of clusters is used during the segmentation process.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
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
An Unsupervised Cluster-based Image Retrieval Algorithm using Relevance FeedbackIJMIT JOURNAL
Content-based image retrieval (CBIR) systems utilize low level query image feature as identifying similarity between a query image and the image database. Image contents are plays significant role for image retrieval. There are three fundamental bases for content-based image retrieval, i.e. visual feature extraction, multidimensional indexing, and retrieval system design. Each image has three contents such as: color, texture and shape features. Color and texture both plays important image visual features used in Content-Based Image Retrieval to improve results. Color histogram and texture features have potential to retrieve similar images on the basis of their properties. As the feature extracted from a query is low level, it is extremely difficult for user to provide an appropriate example in based query. To overcome these problems and reach higher accuracy in CBIR system, providing user with relevance feedback is famous for provide promising solutio
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
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 implementation of novel genetic based clustering algorithm for color image...TELKOMNIKA JOURNAL
The color image segmentation is one of most crucial application in image processing. It can apply to medical image segmentation for a brain tumor and skin cancer detection or color object detection on CCTV traffic video image segmentation and also for face recognition, fingerprint recognition etc. The color image segmentation has faced the problem of multidimensionality. The color image is considered in five-dimensional problems, three dimensions in color (RGB) and two dimensions in geometry (luminosity layer and chromaticity layer). In this paper the, L*a*b color space conversion has been used to reduce the one dimensional and geometrically it converts in the array hence the further one dimension has been reduced. The a*b space is clustered using genetic algorithm process, which minimizes the overall distance of the cluster, which is randomly placed at the start of the segmentation process. The segmentation results of this method give clear segments based on the different color and it can be applied to any application.
A comparative analysis of retrieval techniques in content based image retrievalcsandit
Basic group of visual techniques such as color, shape, texture are used in Content Based Image
Retrievals (CBIR) to retrieve query image or sub region of image to find similar images in
image database. To improve query result, relevance feedback is used many times in CBIR to
help user to express their preference and improve query results. In this paper, a new approach
for image retrieval is proposed which is based on the features such as Color Histogram, Eigen
Values and Match Point. Images from various types of database are first identified by using
edge detection techniques .Once the image is identified, then the image is searched in the
particular database, then all related images are displayed. This will save the retrieval time.
Further to retrieve the precise query image, any of the three techniques are used and
comparison is done w.r.t. average retrieval time. Eigen value technique found to be the best as
compared with other two techniques.
Content Based Image Retrieval (CBIR) is one of the
most active in the current research field of multimedia retrieval.
It retrieves the images from the large databases based on images
feature like color, texture and shape. In this paper, Image
retrieval based on multi feature fusion is achieved by color and
texture features as well as the similarity measures are
investigated. The work of color feature extraction is obtained by
using Quadratic Distance and texture features by using Pyramid
Structure Wavelet Transforms and Gray level co-occurrence
matrix. We are comparing all these methods for best image
retrieval
Content Based Image Retrieval Approach Based on Top-Hat Transform And Modifie...cscpconf
In this paper a robust approach is proposed for content based image retrieval (CBIR) using texture analysis techniques. The proposed approach includes three main steps. In the first one, shape detection is done based on Top-Hat transform to detect and crop object part of the image. Second step is included a texture feature representation algorithm using color local binary patterns (CLBP) and local variance features. Finally, to retrieve mostly closing matching images to the query, log likelihood ratio is used. The performance of the proposed approach is evaluated using Corel and Simplicity image sets and it compared by some of other well-known approaches in terms of precision and recall which shows the superiority of the proposed approach. Low noise sensitivity, rotation invariant, shift invariant, gray scale invariant and low computational complexity are some of other advantages.
Query Image Searching With Integrated Textual and Visual Relevance Feedback f...IJERA Editor
There are many researchers who have studied the relevance feedback in the literature of content based image
retrieval (CBIR) community, but none of CBIR search engines support it because of scalability, effectiveness
and efficiency issues. In this, we had implemented an integrated relevance feedback for retrieving of web
images. Here, we had concentrated on integration of both textual features (TF) and visual features (VF) based
relevance feedback (RF), simultaneously we also tested them individually. The TFRF employs and effective
search result clustering (SRC) algorithm to get salient phrases. Then a new user interface (UI) is proposed to
support RF. Experimental results show that the proposed algorithm is scalable, effective and accurated
Content Based Image Retrieval Using Dominant Color and Texture FeaturesIJMTST Journal
The purpose of this Paper is to describe our research on different feature extraction and matching techniques in designing a Content Based Image Retrieval (CBIR) system. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Content Based Image Retrieval (CBIR) is the retrieval of images based on features such as color and texture. Image retrieval using color feature cannot provide good solution for accuracy and efficiency. The most important features are Color and texture. In this paper technique used for retrieving the images based on their content namely dominant color, texture and combination of both color and texture. The technique verifies the superiority of image retrieval using multi feature than the single feature.
Ijaems apr-2016-16 Active Learning Method for Interactive Image RetrievalINFOGAIN PUBLICATION
With many possible multimedia applications, content-based image retrieval (CBIR) has recently gained more interest for image management and web search. CBIR is a technique that utilizes the visual content of an image, to search for similar images in large-scale image databases, according to a user’s concern. In image retrieval algorithms, retrieval is according to feature similarities with respect to the query, ignoring the similarities among images in database. To use the feature similarities information, this paper presents the k-means clustering algorithm to image retrieval system. This clustering algorithm optimizes the relevance results by firstly clustering the similar images in the database. In this paper, we are also implementing wavelet transform which demonstrates significant rough and precise filtering. We also apply the Euclidean distance metric and input a query image based on similarity features of which we can retrieve the output images. The results show that the proposed approach can greatly improve the efficiency and performances of image retrieval.
The development of multimedia system technology in Content based Image Retrieval (CBIR) System is
one in every of the outstanding area to retrieve the images from an oversized collection of database. The feature
vectors of the query image are compared with feature vectors of the database images to get matching images.It is
much observed that anyone algorithm isn't beneficial in extracting all differing kinds of natural images. Thus an
intensive analysis of certain color, texture and shape extraction techniques are allotted to spot an efficient CBIR
technique that suits for a selected sort of images. The Extraction of an image includes feature description and
feature extraction. During this paper, we tend to projected Color Layout Descriptor (CLD), grey Level Co-
Occurrences Matrix (GLCM), Marker-Controlled Watershed Segmentation feature extraction technique that
extract the matching image based on the similarity of Color, Texture and shape within the database. For
performance analysis, the image retrieval timing results of the projected technique is calculated and compared
with every of the individual feature.
Evaluation of Euclidean and Manhanttan Metrics In Content Based Image Retriev...IJERA Editor
Content-based Image Retrieval is all about generating signatures of images in database and comparing the signature of the query image with these stored signatures. Color histogram can be used as signature of an image and used to compare two images based on certain distance metric. Distance metrics Manhattan distance (L1 norm) and Euclidean distance (L2 norm) are used to determine similarities between a pair of images. In this paper, Corel database is used to evaluate the performance of Manhattan and Euclidean distance metrics. The experimental results showed that Manhattan showed better precision rate than Euclidean distance metric. The evaluation is made using Content based image retrieval application developed using color moments of the Hue, Saturation and Value(HSV) of the image and Gabor descriptors are adopted as texture features.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
SEMANTIC IMAGE RETRIEVAL USING MULTIPLE FEATUREScscpconf
In Content Based Image Retrieval (CBIR) some problem such as recognizing the similar
images, the need for databases, the semantic gap, and retrieving the desired images from huge
collections are the keys to improve. CBIR system analyzes the image content for indexing,
management, extraction and retrieval via low-level features such as color, texture and shape.
To achieve higher semantic performance, recent system seeks to combine the low-level features
of images with high-level features that conation perceptual information for human beings.
Performance improvements of indexing and retrieval play an important role for providing
advanced CBIR services. To overcome these above problems, a new query-by-image technique
using combination of multiple features is proposed. The proposed technique efficiently sifts through the dataset of images to retrieve semantically similar images.
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
An Unsupervised Cluster-based Image Retrieval Algorithm using Relevance FeedbackIJMIT JOURNAL
Content-based image retrieval (CBIR) systems utilize low level query image feature as identifying similarity between a query image and the image database. Image contents are plays significant role for image retrieval. There are three fundamental bases for content-based image retrieval, i.e. visual feature extraction, multidimensional indexing, and retrieval system design. Each image has three contents such as: color, texture and shape features. Color and texture both plays important image visual features used in Content-Based Image Retrieval to improve results. Color histogram and texture features have potential to retrieve similar images on the basis of their properties. As the feature extracted from a query is low level, it is extremely difficult for user to provide an appropriate example in based query. To overcome these problems and reach higher accuracy in CBIR system, providing user with relevance feedback is famous for provide promising solutio
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
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 implementation of novel genetic based clustering algorithm for color image...TELKOMNIKA JOURNAL
The color image segmentation is one of most crucial application in image processing. It can apply to medical image segmentation for a brain tumor and skin cancer detection or color object detection on CCTV traffic video image segmentation and also for face recognition, fingerprint recognition etc. The color image segmentation has faced the problem of multidimensionality. The color image is considered in five-dimensional problems, three dimensions in color (RGB) and two dimensions in geometry (luminosity layer and chromaticity layer). In this paper the, L*a*b color space conversion has been used to reduce the one dimensional and geometrically it converts in the array hence the further one dimension has been reduced. The a*b space is clustered using genetic algorithm process, which minimizes the overall distance of the cluster, which is randomly placed at the start of the segmentation process. The segmentation results of this method give clear segments based on the different color and it can be applied to any application.
A comparative analysis of retrieval techniques in content based image retrievalcsandit
Basic group of visual techniques such as color, shape, texture are used in Content Based Image
Retrievals (CBIR) to retrieve query image or sub region of image to find similar images in
image database. To improve query result, relevance feedback is used many times in CBIR to
help user to express their preference and improve query results. In this paper, a new approach
for image retrieval is proposed which is based on the features such as Color Histogram, Eigen
Values and Match Point. Images from various types of database are first identified by using
edge detection techniques .Once the image is identified, then the image is searched in the
particular database, then all related images are displayed. This will save the retrieval time.
Further to retrieve the precise query image, any of the three techniques are used and
comparison is done w.r.t. average retrieval time. Eigen value technique found to be the best as
compared with other two techniques.
Content Based Image Retrieval (CBIR) is one of the
most active in the current research field of multimedia retrieval.
It retrieves the images from the large databases based on images
feature like color, texture and shape. In this paper, Image
retrieval based on multi feature fusion is achieved by color and
texture features as well as the similarity measures are
investigated. The work of color feature extraction is obtained by
using Quadratic Distance and texture features by using Pyramid
Structure Wavelet Transforms and Gray level co-occurrence
matrix. We are comparing all these methods for best image
retrieval
Content Based Image Retrieval Approach Based on Top-Hat Transform And Modifie...cscpconf
In this paper a robust approach is proposed for content based image retrieval (CBIR) using texture analysis techniques. The proposed approach includes three main steps. In the first one, shape detection is done based on Top-Hat transform to detect and crop object part of the image. Second step is included a texture feature representation algorithm using color local binary patterns (CLBP) and local variance features. Finally, to retrieve mostly closing matching images to the query, log likelihood ratio is used. The performance of the proposed approach is evaluated using Corel and Simplicity image sets and it compared by some of other well-known approaches in terms of precision and recall which shows the superiority of the proposed approach. Low noise sensitivity, rotation invariant, shift invariant, gray scale invariant and low computational complexity are some of other advantages.
Query Image Searching With Integrated Textual and Visual Relevance Feedback f...IJERA Editor
There are many researchers who have studied the relevance feedback in the literature of content based image
retrieval (CBIR) community, but none of CBIR search engines support it because of scalability, effectiveness
and efficiency issues. In this, we had implemented an integrated relevance feedback for retrieving of web
images. Here, we had concentrated on integration of both textual features (TF) and visual features (VF) based
relevance feedback (RF), simultaneously we also tested them individually. The TFRF employs and effective
search result clustering (SRC) algorithm to get salient phrases. Then a new user interface (UI) is proposed to
support RF. Experimental results show that the proposed algorithm is scalable, effective and accurated
Content Based Image Retrieval Using Dominant Color and Texture FeaturesIJMTST Journal
The purpose of this Paper is to describe our research on different feature extraction and matching techniques in designing a Content Based Image Retrieval (CBIR) system. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Content Based Image Retrieval (CBIR) is the retrieval of images based on features such as color and texture. Image retrieval using color feature cannot provide good solution for accuracy and efficiency. The most important features are Color and texture. In this paper technique used for retrieving the images based on their content namely dominant color, texture and combination of both color and texture. The technique verifies the superiority of image retrieval using multi feature than the single feature.
Ijaems apr-2016-16 Active Learning Method for Interactive Image RetrievalINFOGAIN PUBLICATION
With many possible multimedia applications, content-based image retrieval (CBIR) has recently gained more interest for image management and web search. CBIR is a technique that utilizes the visual content of an image, to search for similar images in large-scale image databases, according to a user’s concern. In image retrieval algorithms, retrieval is according to feature similarities with respect to the query, ignoring the similarities among images in database. To use the feature similarities information, this paper presents the k-means clustering algorithm to image retrieval system. This clustering algorithm optimizes the relevance results by firstly clustering the similar images in the database. In this paper, we are also implementing wavelet transform which demonstrates significant rough and precise filtering. We also apply the Euclidean distance metric and input a query image based on similarity features of which we can retrieve the output images. The results show that the proposed approach can greatly improve the efficiency and performances of image retrieval.
The development of multimedia system technology in Content based Image Retrieval (CBIR) System is
one in every of the outstanding area to retrieve the images from an oversized collection of database. The feature
vectors of the query image are compared with feature vectors of the database images to get matching images.It is
much observed that anyone algorithm isn't beneficial in extracting all differing kinds of natural images. Thus an
intensive analysis of certain color, texture and shape extraction techniques are allotted to spot an efficient CBIR
technique that suits for a selected sort of images. The Extraction of an image includes feature description and
feature extraction. During this paper, we tend to projected Color Layout Descriptor (CLD), grey Level Co-
Occurrences Matrix (GLCM), Marker-Controlled Watershed Segmentation feature extraction technique that
extract the matching image based on the similarity of Color, Texture and shape within the database. For
performance analysis, the image retrieval timing results of the projected technique is calculated and compared
with every of the individual feature.
Evaluation of Euclidean and Manhanttan Metrics In Content Based Image Retriev...IJERA Editor
Content-based Image Retrieval is all about generating signatures of images in database and comparing the signature of the query image with these stored signatures. Color histogram can be used as signature of an image and used to compare two images based on certain distance metric. Distance metrics Manhattan distance (L1 norm) and Euclidean distance (L2 norm) are used to determine similarities between a pair of images. In this paper, Corel database is used to evaluate the performance of Manhattan and Euclidean distance metrics. The experimental results showed that Manhattan showed better precision rate than Euclidean distance metric. The evaluation is made using Content based image retrieval application developed using color moments of the Hue, Saturation and Value(HSV) of the image and Gabor descriptors are adopted as texture features.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
SEMANTIC IMAGE RETRIEVAL USING MULTIPLE FEATUREScscpconf
In Content Based Image Retrieval (CBIR) some problem such as recognizing the similar
images, the need for databases, the semantic gap, and retrieving the desired images from huge
collections are the keys to improve. CBIR system analyzes the image content for indexing,
management, extraction and retrieval via low-level features such as color, texture and shape.
To achieve higher semantic performance, recent system seeks to combine the low-level features
of images with high-level features that conation perceptual information for human beings.
Performance improvements of indexing and retrieval play an important role for providing
advanced CBIR services. To overcome these above problems, a new query-by-image technique
using combination of multiple features is proposed. The proposed technique efficiently sifts through the dataset of images to retrieve semantically similar images.
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.
Invention of digital technology has lead to increase in the number of images that can be stored in digital format. So searching and retrieving images in large image databases has become more challenging. From the last few years, Content Based Image Retrieval (CBIR) gained increasing attention from researcher. CBIR is a system which uses visual features of image to search user required image from large image
database and user’s requests in the form of a query image. Important features of images are colour, texture and shape which give detailed information about the image. CBIR techniques using different feature extraction techniques are discussed in this paper.
Content Based Image Retrieval : Classification Using Neural Networksijma
In a content-based image retrieval system (CBIR), the main issue is to extract the image features that
effectively represent the image contents in a database. Such an extraction requires a detailed evaluation of
retrieval performance of image features. This paper presents a review of fundamental aspects of content
based image retrieval including feature extraction of color and texture features. Commonly used color
features including color moments, color histogram and color correlogram and Gabor texture are
compared. The paper reviews the increase in efficiency of image retrieval when the color and texture
features are combined. The similarity measures based on which matches are made and images are
retrieved are also discussed. For effective indexing and fast searching of images based on visual features,
neural network based pattern learning can be used to achieve effective classification.
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
DOMAIN SPECIFIC CBIR FOR HIGHLY TEXTURED IMAGEScseij
It is A Challenging Task To Build A Cbir System Which Primarily Works On Texture Values As There
Meaning And Semantics Needs A Special Care To Be Mapped With Human Based Languages. We Have
Consider Highly Textured Images Having Properties(Entropy, Homogeneity, Contrast, Cluster Shade, Auto
Correlation)And Have Mapped Using A Fuzzy Minmax Scale W.R.T. Their Degree(High, Low,
Medium)And Technical Interpetation.This Developed System Is Performing Well In Terms Of Precision
And Recall Value Showing That Semantic Gap Has Been Reduced For Highly Textured Images Based Cbir.
A COMPARATIVE ANALYSIS OF RETRIEVAL TECHNIQUES IN CONTENT BASED IMAGE RETRIEVALcscpconf
Basic group of visual techniques such as color, shape, texture are used in Content Based Image Retrievals (CBIR) to retrieve query image or sub region of image to find similar images in image database. To improve query result, relevance feedback is used many times in CBIR to help user to express their preference and improve query results. In this paper, a new approach for image retrieval is proposed which is based on the features such as Color Histogram, Eigen Values and Match Point. Images from various types of database are first identified by using edge detection techniques .Once the image is identified, then the image is searched in the particular database, then all related images are displayed. This will save the retrieval time. Further to retrieve the precise query image, any of the three techniques are used and comparison is done w.r.t. average retrieval time. Eigen value technique found to be the best as compared with other two techniques.
Wavelet-Based Color Histogram on Content-Based Image RetrievalTELKOMNIKA JOURNAL
The growth of image databases in many domains, including fashion, biometric, graphic design,
architecture, etc. has increased rapidly. Content Based Image Retrieval System (CBIR) is a technique used
for finding relevant images from those huge and unannotated image databases based on low-level features
of the query images. In this study, an attempt to employ 2nd level Wavelet Based Color Histogram (WBCH)
on a CBIR system is proposed. Image database used in this study are taken from Wang’s image database
containing 1000 color images. The experiment results show that 2nd level WBCH gives better precision
(0.777) than the other methods, including 1st level WBCH, Color Histogram, Color Co-occurrence Matrix,
and Wavelet texture feature. It can be concluded that the 2nd Level of WBCH can be applied to CBIR system.
A Survey of Image Segmentation based on Artificial Intelligence and Evolution...IOSR Journals
Abstract : In image analysis, segmentation is the partitioning of a digital image into multiple regions (sets of
pixels), according to some homogeneity criterion. The problem of segmentation is a well-studied one in
literature and there are a wide variety of approaches that are used. Different approaches are suited to different
types of images and the quality of output of a particular algorithm is difficult to measure quantitatively due to
the fact that there may be much correct segmentation for a single image. Image segmentation denotes a process
by which a raw input image is partitioned into nonoverlapping regions such that each region is homogeneous
and the union of any two adjacent regions is heterogeneous. A segmented image is considered to be the highest
domain-independent abstraction of an input image. Image segmentation is an important processing step in many
image, video and computer vision applications. Extensive research has been done in creating many different
approaches and algorithms for image segmentation, but it is still difficult to assess whether one algorithm
produces more accurate segmentations than another, whether it be for a particular image or set of images, or
more generally, for a whole class of images.
In this paper, The Survey of Image Segmentation using Artificial Intelligence and Evolutionary Approach
methods that have been proposed in the literature. The rest of the paper is organized as follows. 1.
Introduction, 2.Literature review, 3.Noteworthy contributions in the field of proposed work, 4.Proposed
Methodology, 5.Expected outcome of the proposed research work, 6.Conclusion.
Keywords: Image Segmentation, Segmentation Algorithm, Artificial Intelligence, Evolutionary Algorithm,
Neural Network, Fuzzy Set, Clustering.
EFFECTIVE SEARCH OF COLOR-SPATIAL IMAGE USING SEMANTIC INDEXINGIJCSEA Journal
Most of the data stored in libraries are in digital form will contain either pictures or video, which is tough to search or browse. Methods which are automatic for searching picture collections made large use of color histograms, because they are very strong to wide changes in viewpoint, and can be calculated trivially. However, color histograms unable to present spatial data, and therefore tend to give lesser results. By using combination of color information with spatial layout we have developed several methods, while retrieving the advantages of histograms. A method computes a given color as a function of the distance between two pixels, which we call a color correlogram. We propose a color-based image descriptor that can be used for image indexing based on high-level semantic concepts. The descriptor is
based on Kobayashi’s Color Image Scale, which is a system that includes 130 basic colors combined in 1180 three-color combinations. The words are represented in a two dimensional semantic space into groups based on perceived similarity. The modified approach for statistical analysis of pictures involves transformations of ordinary RGB histograms. Then a semantic image descriptor is derived, containing semantic data about both color combinations and single colors in the image.
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.
Multi Resolution features of Content Based Image RetrievalIDES Editor
Many content based retrieval systems have been
proposed to manage and retrieve images on the basis of their
content. In this paper we proposed Color Histogram, Discrete
Wavelet Transform and Complex Wavelet Transform
techniques for efficient image retrieval from huge database.
Color Histogram technique is based on exact matching of
histogram of query image and database. Discrete Wavelet
transform technique retrieves images based on computation
of wavelet coefficients of subbands. Complex Wavelet
Transform technique includes computation of real and
imaginary part to extract the details from texture. The
proposed method is tested on COREL1000 database and
retrieval results have demonstrated a significant improvement
in precision and recall.
Combining Generative And Discriminative Classifiers For Semantic Automatic Im...CSCJournals
The object image annotation problem is basically a classification problem and there are many different modeling approaches for the solution. These approaches can be classified into two main categories such as generative and discriminative. An ideal classifier should combine these two complementary approaches. In this paper, we present a method achieving this combination by using the discriminative power of the neural networks and the generative nature of Bayesian networks. The evaluation of the proposed method on three typical image’s database has shown some success in automatic image annotation.
Textural Feature Extraction of Natural Objects for Image ClassificationCSCJournals
The field of digital image processing has been growing in scope in the recent years. A digital image is represented as a two-dimensional array of pixels, where each pixel has the intensity and location information. Analysis of digital images involves extraction of meaningful information from them, based on certain requirements. Digital Image Analysis requires the extraction of features, transforms the data in the high-dimensional space to a space of fewer dimensions. Feature vectors are n-dimensional vectors of numerical features used to represent an object. We have used Haralick features to classify various images using different classification algorithms like Support Vector Machines (SVM), Logistic Classifier, Random Forests Multi Layer Perception and Naïve Bayes Classifier. Then we used cross validation to assess how well a classifier works for a generalized data set, as compared to the classifications obtained during training.
Similar to A comparative study on content based image retrieval methods (20)
Lithological Investigation at Tombia and Opolo Using Vertical Electrical Soun...IJLT EMAS
Vertical electrical soundings (VES) was carried out in Opolo and Tombia all in Yenagoa local government area, Bayelsa state, Nigeria to understand the resistivity distribution of its subsurface which serves as a tool in investigating subsurface lithology. All VES sounding were stacked together to generate 1D pseudo tomogram and was subsequently interpreted. The interpreted VES curve results shows that Opolo consists of three layers within the depth of investigation. Sandy clay with mixture of silt make up the first layer (Top layer) with resistance value ranging from 24-63Ωm. The second layer is made up of thick clay with very low resistivity values ranging from 3-19Ωm. The third layer is sandyclay with its resistance value ranging from 26-727Ωm.Tombia also reveals that the area is in three layers within the depth of investigation. Sandy clay with a mixture of fine sand made up the first layer (Top soil) with its resistance values ranging from 40-1194Ωm. The second layer is made up of fine sand with resistivity value ranging from 475-5285Ωm. The third layer is made up of sandy clay/sand with its resistance value ranging from 24-28943Ωm.The results of the 1D pseudo tomogram also reveals that Tombia and Opolo consists of three layers within the depth of investigation and pseudo tomograms serves as a basis tool for interpreting lithology and identifying lithological boundaries for the subsurface
Public Health Implications of Locally Femented Milk (Nono) and Antibiotic Sus...IJLT EMAS
The study is to determine the PH and moisture content
of Nono sold in Port Harcourt , the prevalence of Pseudomonas
aeruginosa in Fura da nono and finally the antibiotic resistance
pattern of Pseudomonas aeruginosa isolated from the fermented
products. nono samples were purchased from Borikiri in
portharcourt township. A total of 20 samples were assessed to
determine their microbiological quality and to conduct antibiotic
susceptibility test. Moisture content and pH of the samples were
also assessed. Enumeration of the total viable bacterial count
(TVBC), Total coliform count (TCC) and Total Pseudomonal
count (TPC) were also assessed to determine the sanitary quality
of the product. The PH ranges between 2.99 to 3.89 while the
moisture content ranges between 80% to 88%. The result
obtained from the microbial culture indicated that a wide array
of microorganism were present in Fura da nono including species
of Bacilu, klebsiella, Pseudomonas Staphylococcus aureus,
Streptococcus, Lactobacillus and Escherichia coli.. The highest
TVBC, TCC and TPC were 9.8x103
cfu/ml, 10x103
cfu/ml and
9.7x103
cfu/ml respectively. Antibiotic susceptibility was
conducted using 12 broad spectrum antibiotics and compared
against a standard provided by the Clinical laboratory standard
institute (CLSI). Gentamycin, Ofloxacin and Levofloxacin
recorded 100% resistance , while Cotrimoxazole, Ciprofloxacin,
Vancomycin, Nitrofurantoin, Norfloxacin and Azithromycin
recorded 100% susceptibility as indicated by the complete clear
zone of inhibition.It was discovered that the absence of
regulatory agencies like National Agency for Food Drug
Administration and Control (NAFDAC) in the regulation of the
quality of the product was the cause of the high contamination,
since there were no quality control measures in its production
line .It was recommended that NAFDAC should provide a
standard operating procedure for local food producers and
should include them in their scope for regulation.
Bioremediation Potentials of Hydrocarbonoclastic Bacteria Indigenous in the O...IJLT EMAS
Hydrocarbon pollution Remediation by Enhanced
Natural Attenuation method was adopted to remediate the
hydrocarbon impacted site in Ogoniland Rivers State, Nigeria .
The research lasted for 6 months. Samples were collected at
monthly intervals . samples were collected intermittently
between Feb 2019 to July 2019 . Mineral salt medium containing
crude oil was used as a sole source of carbon and energy for the
isolation of hydrocarbonoclastic bacteria. Samples were
collected from the four (4) local government that made up
Ogoniland and they includes Khana(k), Gokana (G),Tai (T),
Eleme (E) and transported immediately to the laboratory for
analysis. The microbial and physicochemical properties of the
soil samples varied with the different local government areas.
Seven bacteria genera were isolated from the samples from the
four locations, viz, Pseudomonas, Lactobacter, Micrococcus,
Arthrobacter, Bacillus, Brevibacterium and Mycobacterium
were isolated and identified. the seven isolate were indigenous in
the study area. Nutrient were added to identified plots of
hydrocarbon pollution polluted site within the four local
government and they were able degrade hydrocarbon within a
short of period of time. Reassessment of physicochemical
parameter impacted site was used to judge the bioremediation
potentials of microorganism
Comparison of Concurrent Mobile OS CharacteristicsIJLT EMAS
It is challenging for the mobile industry to supply the best features of the devices with its increasing customer requirements. Among the progress of technologies, the mobile industry is the fastest growing; as it keeps pace with rapidly changing market demands. This paper compares between the currently available mobile devices based on its user interface, security, memory utilization, processor, and device architecture. The mobile products launched from 2015-19 are used for comparison. Current results after comparison with earlier study found that many mobile devices and features became obsolete in a short time span supporting the aggressive growth of mobile industry.
Design of Complex Adders and Parity Generators Using Reversible GatesIJLT EMAS
This paper shows efficient design of an odd and even parity generator, a 4-bit ripple carry adder, and a 2-bit carry look ahead adder using reversible gates. Number of reversible gates used, garbage output, and percentage usage of outputs in implementing each combinational circuit is derived. The CLA used 10 reversible gates with 14 garbage outputs, with 50% percentage performance usage.
Design of Multiplexers, Decoder and a Full Subtractor using Reversible GatesIJLT EMAS
This paper shows an effective design of combinational circuits such as 2:1, 4:1 multiplexers, 2:4 decoder and a full subtractor using reversible gates. This paper also evaluates number of reversible gates used and garbage outputs in implementing each combinational circuit.
Multistage Classification of Alzheimer’s DiseaseIJLT EMAS
Alzheimer’s disease is a type of dementia that destroys
memory and other mental functions. During the progression of
the disease certain proteins called plaques and tangles get
deposited in hippocampus which is located in the temporal lobe
of brain. The disease is not a normal part of aging and gets
worsen over time. Medical imaging techniques like Magnetic
Resonance Imaging (MRI), Computed Tomography (CT) and
Positron Emission Tomography (PET) play significant role in the
disease diagnosis. In this paper, we propose a method for
classifying MRI into Normal Control (NC), Mild Cognitive
Impairment (MCI) and Alzheimer’s Disease(AD). An overall
outline of the methodology includes textural feature extraction,
feature reduction process and classification of the images into
various stages. Classification has been performed with three
classifiers namely Support Vector Machine (SVM), Artificial
Neural Network (ANN) and k-Nearest Neighbours (k-NN)
Design and Analysis of Disc Brake for Low Brake SquealIJLT EMAS
Vibration induced due to friction in disc brake is a
theme of major interest and related to the automotive industry.
Squeal noise generated during braking action is an indication of
a complicated dynamic problem which automobile industries
have faced for decades. For the current study, disc brake of 150
cc is considered. Vibration and sound level for different speed
are measured. Finite element and experimentation for modal
analysis of different element of disc brake and assembly are
carried out. In order to check that precision of the finite element
with those of experimentation, two stages are used both
component level and assembly level. Mesh sensitivity of the disc
brake component is considered. FE updating is utilized to reduce
the relative errors between the two measurements by tuning the
material. Different viscoelastic materials are selected and
constrained layer damping is designed. Constrained layer
damping applied on the back side of friction pads and compared
vibration and sound level of disc brake assembly without
constrained layer damping with disc brake assembly having
constrained layer. It was observed that there were reduction in
vibration and sound level. Nitrile rubber is most effective
material for constrained layer damping.
The aim of this article is to device strategies for
establishing and managing tomato processing industry, which
aims to enhance the taste experiences on different tomato
products for the people. Management needed for a successful
business is analyzed in each and every aspect. The five important
steps in management- planning, organizing, staffing, leading and
controlling are applied in management of the industry. Planning-
In the planning process, activities required to achieve desired
goals are thought about. This process involves the creation and
maintenance of a plan, those include psychological aspects that
require conceptual skills. Organizing- Organizing is a systematic
processing in order to attain objectives of structuring,
integrating, co-ordinating task, and activities. Staffing- Staffing is
the process of acquiring, deploying, and retaining a workforce of
sufficient quantity and quality to create positive impacts on the
organization’s effectiveness. Leading- Communicating,
motivating, inspiring and encouraging employees are key aspects
of process of leading, task of which is towards a higher level of
productivity of organization. Controlling- Controlling measures
the deviation of actual performance from the standard
performance, discovers the causes of such deviations and helps in
taking corrective actions.
This paper deals with the functioning of a Propylene
Recovery Unit (PRU) in a chemical industry and the various
Managerial and Human Resource considerations that need to be
accounted for, in this process. This report discusses various
aspects that are to be considered, before initializing the setup of
PRU, ranging from a Management perspective. Mission and
objective was decided and subsequently the managerial model
was developed. Propylene is an indispensible raw material that
has a variety of end use. A detailed analysis pertaining to
propylene demand in the market along with major sources has
been incorporated in this paper. Emphasis has been placed on
the type of departmentation required. Managerial aspects of
various functions ranging from warehousing to quality control
have also been taken into consideration. Delegations of functional
departments have been defined to prevent redundancy of duties
and major managerial functions of Planning, Organizing,
Staffing, Leading and Controlling has also been discussed.
Internal and External factors that affect the company have been
analyzed through SWOT Analysis and MBO strategies are also
broadly classified. Finally, Total Quality Management and
strategies for adoption of Lean Manufacturing as also touched
upon briefly.
This business model is intended to provide an online
platform connecting the general public customers with the
producers of groceries and food products such as fruits,
vegetables, meat and dairy products. The producers are selected
based on their production methods and their quality. The model
obtains the demand from the customers and the supply is found
from the producers. The prices of the products are fixed
according to the supply and demand. The customers' orders can
be classified into two different categories: 1. Bulk orders and 2.
Recipe based. The orders are obtained in a bulk quantity or for a
certain period of time and the products are delivered
periodically as per the customer's need. This model eliminates
the requirements of conventional storage units and also controls
the quality of the products using scientific devices. This model
reduces the wastage of resources as it enables the customer to
estimate their requirements using the help of recipe based
ordering system and also keeps the price constant for the bulk
orders.
Home textile exports are market driven, which implies that they deal with what the foreign market wants and how the home textile exporter could fulfil it, or product driven, where they deal with what the exporter has to offer and how can an appropriate strategy be applied to find the targeted buyers in the foreign market. The requisites of these are that the exporter must know the export plan, production procedure and export documentations. Exporter also must know his/her operational capacity, organizational nature and structure. An attempt is made in this project to understand and examine the nature and structure of the organization of the S3P exports.
Almost 80% of the population are coffee lovers.
Kaffinite sunshine café is guaranteed to become the daily
necessity for all the coffee addicts. A place with good ambience
where people can escape from their daily stress and cherish with
a morning cup of coffee. Our café offers home style delicious
breakfast and snacks. We focus on finding the most aromatic
and exotic coffee beans. We have our branches in many cities of
Tamil Nadu. We have a romantic ambience which attracts youth.
Our café has spectacular interior designs with stupendous taste
of coffee. We have attached our menu which contains multicuisines
at attractive prices. In this paper, we have done SWOT
analysis of our café to know our strengths and weaknesses. We
have also analyzed our opportunities and threats from the
external environment
Management of a Paper Manufacturing IndustryIJLT EMAS
This project focuses on how a paper manufacturing industry looks like and how it operates. For better understanding purpose, we have taken a hypothetical situation here. We have discussed on various factors that are to be considered before constructing a plant. For example, what kind of proprietorship is suitable for this case? We have developed a SWOT Analysis for the plant, thinking about the pros and cons. This project can be a guide for a person who is willing to start up a new manufacturing plant. This report can be used to streamline your approach to planning by outlining the responsibilities of plant managers and external factors, as well as identifying appropriate resources to assist you with the construction of plant.
Application of Big Data Systems to Airline ManagementIJLT EMAS
The business world is in the midst of the next
revolution following the IT revolution – the Big Data revolution.
The sheer volume of data produced is a major reason for the big
data revolution. Aviation and aerospace are typical areas that
can apply big data systems due to the scale of data produced, not
only by the plane sensors and passengers, but also by the
prospective passengers. Data that need to be considered include,
but are not limited to, aircraft sensor data, passenger data,
weather data, aircraft maintenance data and air traffic data.
This paper aims at identifying areas in aviation where big data
systems can be utilized to enhance operational performances
improve customer relations and thereby aiding the ultimate goal
of increased profits at reduced costs. An improved management
model built on a strong big data infrastructure will reduce
operation costs, improve safety, bring down the cost and time
spent on maintenance and drastically improve customer
relations.
Impact of Organisational behaviour and HR Practices on Employee Retention in ...IJLT EMAS
I. INTRODUCTION
Roads are constituted as the most significant component of
India‟s Logistics Industry, accounting for 60 percent of
the total freight movement in the country. A majority of
players in this industry are small entrepreneurs running their
family businesses. As a result, Man Power Development
Investments that pay off in the longer term, have been
minimised respectively. Moreover, these businesses are
typically controlled severely by the proprietor and his / her
family and consequently, making it unattractive for the
professionals. Poor working conditions, Low pay scales
relative to alternate careers, poor or non-existent Manpower
Policies and prevalence of unscrupulous practices have added
to the segment's woes for seeking employment. Thus, it could
be rightly stated that the Transportation, Logistics,
Warehousing and Packaging Sector is considered an
unattractive career option and fails to attract and retain skilled
manpower. Many Organizations have failed to recognize that
Human Resources play an important role in gaining an
immense advantage in today‟s highly competitive Global
Business Environment. While all aspects of managing Human
Resources is important, Employee Retention continues to be
an essential part of Human Resource Management activity
that help the Organizations to achieve their goals and
objectives.
Sustainable Methods used to reduce the Energy Consumption by Various Faciliti...IJLT EMAS
The purpose of this article is to identify the energy
challenges faced by airports especially with regards to the energy
consumed by the terminal building and suggest suitable energy
conservation techniques based on what has already been
implemented in few airports around the world.
We have identified the various facilities and systems which are
responsible for a major share of the consumption of energy by
airport terminals and we have suggested measures to effectively
overcome these problems.
OVERVIEW OF THE COMPANY
Cake Walk sweets and savories
Cake Walk is India‟s No. 1 confectionery and cake
manufacturer with its products exported to over 20 countries
around the world. They are dedicated to the art of producing
innovative and delicious products for sweet lovers of all ages.
Cake Walk‟s products offer tantalizing experiences that sparks
the imagination in people who eat their candy. Of course, this
has been Cake Walk‟s goal since their inception in 1947.
Today, Cake Walk Candy continues to make some of the best
candy in India. They also are a responsible business venture
and contribute positively to the society with their “Learn to
bake” initiative to encourage households to earn by starting
their own small-scale businesses. Cake Walk products can be
enjoyed by kids and adults alike, and their products come in
an array of flavors, shapes and sizes.
Every individual in our planet is busy in his / her own
world these days. The busy schedules and work preoccupations
of many people hinder them from spending nominal amount of
time with their families.
To address this concern, we have come up with our MACH
Tours and Travels, our motto being, “Breaching the
Boundaries!” which aims at not only giving its customers the best
and most comfortable tour, but also an enjoyable and
memorable experiences.
We differ from our competitors in various ways. For a start, we
emphasize that our profit is not in the income from this business,
but in the satisfaction of our customers. Added to that, we focus
on improving the ease of travel, the luxury of trip, the quality of
time spent and the worth of pay.
There is a variety of customers we come across: some will want
their trip to be extravagant, while some require it to be cost
effective; some need a long vacation, while some choose just a
weekend away.
Our mission: In order to meet the desires of this large range of
people and to include all the factors of a hearty holiday, we have
devised our strategies and planned our processes, thus, setting us
apart from the others.
Our vision: As the main priority, a year from now, we target on
contenting as many customers as possible through our services.
The following sections of this document includes our roles in
planning, decision making, staffing, leading and communicating
in which we highlight various aspects of our organization,
including the pros and cons of travelling with us.
The purpose of this paper is to highlight the general
terms and definitions that falls under the ‘common set’ in the
intersection of the sets Meteorology and Aerospace Engineering.
It begins with the universal explanations for the meteorological
phenomena under the ‘common set’ followed by the
categorization of clouds and their influences on the aerial
vehicles, the instrumentation used in Aeronautics to determine
the required Meteorological quantities, factors affecting aviation,
effects of aviation on the clouds, and the corresponding protocols
involved in deciphering the ‘common set’ elements.
It also talks about the relation between airport construction and
Geology prior to concluding with the uses and successes of
Meteorology in the field of Aerospace.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
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About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
A comparative study on content based image retrieval methods
1. International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Volume VI, Issue IV, April 2017 | ISSN 2278-2540
www.ijltemas.in Page 77
A Comparative Study on Content Based Image
Retrieval Methods
Kratika Arora, Ashwani Kumar
Sant Longowal Institute of Engineering and Technology, Longowal, Punjab, India.
Abstract— Content-based image retrieval (CBIR) is a method of
finding images from a huge image database according to persons’
interests. Content-based here means that the search involves
analysis the actual content present in the image. As database of
images is growing daybyday, researchers/scholars are searching
for better techniques for retrieval of images maintaining good
efficiency. This paper presents the visual features and various
ways for image retrieval from the huge image database.
Keywords—CBIR, correlogram, feature extraction, descriptors,
relevance feedback.
I. INTRODUCTION
apidly growing in technology day by day, has led to the
increase in multimedia files, digital images and visual
objects. Advancement in medical field and in many other
technologies has given rise to extensive images, their memory
requirement and transmission capability. Increase in the usage
of images in various areas, has led researchers to focus on new
ways [1] by which images can be quickly and efficiently
retrieved and from the large databases. So the mechanism of
image processing and retrieval of the desired image from the
large image database has become an serious task. For many
years, researchers have been working on retrieval processes.
Content-based image retrieval [2] is the modern image retrieval
system. In CBIR retrieval system, different techniques are
brought together for the same purpose as image retrieval,
information processing, and database communities. [3]In a
general content-based image retrieval system(Fig. 1), the visual
content present in the image, in the database is extracted and is
described by a feature vector. The content can be s, texture,
shape or any other useful information that can be derived from
the image.For the image retrieval, user provides the retrieval
system with sample images or figures. System then internally
changes these samples into its feature vectors. The similarity
between the images is determined by calculating the distance
between the feature vectors of the query sample or the sketch
and those of the images present in the database. Image retrieval
is then done with the aid of an indexing scheme. Relevance
feedback is also used in CBIR in order to generate semantically
more and better meaningful retrieval results.
Fig. 1. Block Diagram of CBIR
II. IMAGE CONTENT DESCRIPTORS
Image content can be classified as visual and semantic. Visual
content is very generic or area specific. Generally the visual
content of the image means the colour, texture, and shape. Area
specific visual content is application dependent like human
eyes, faces and it may involve some field knowledge. This
paper focuses on general visual content descriptors. A proper
descriptor must be invariable to the variation which is
introduced accidentally by the process (e.g., illuminance
variation). Also, a visual descriptor can be local or global. A
local descriptor uses the visual features of part/area or objects
in the image for the description of the image content whereas
global descriptor use visual features of the complete image.
Below section presents some techniques which are used widely
for the extraction of colour, texture and shape from the image.
A. COLOR
The color features are extensively used features in image
processing, as their extraction is easy compared to extraction of
image tex. and shape. Colour is comparatively robust and is
also independent of image size and orientation. The following
sections presents commonly used techniques for extraction of
color : color moments, color histogram and color correlogram.
R
2. International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Volume VI, Issue IV, April 2017 | ISSN 2278-2540
www.ijltemas.in Page 78
1. Color Moments
Color moments are being used successfully in many CBIR
systems [4] mainly when image has only the object. These have
been efficient in representation of colour distributions of
images. In this,1st order (mean), 2nd order (variance) and 3rd
order (skewness), are calculated.
Mathematically, these 3 moments are defined as:
Er,i = ij (1)
σr,i = ( i,j - Er,i )2
)1/2
(2)
Sr,i = ( i,j - Er,i )3
)1/3
(3)
where N represents no. of pixels present in the image and Iij
represents the value of i-th colour component for the image
pixel j. Using the 3rd
-order moment in addition i.e skewness,
compared to using only the 1st
and 2nd
order moments improves
the performance. But sometimes it makes the representation
more sensitive and illumination changes and decreasing the
overall performance.
Since, only 9 numbers (3 moments for each of the 3 color
components) has been used to represent the colour content of
every image, colour moments becomes a packed representation
compared to all other colour methods. Due to the packedness, it
may decrease the discrimination power. Hence, color moments
is often used as the 1st
pass to narrow down the search before
using other colour extraction methods for retrieval.
2. Color Histogram
Histogram gives the distribution of number of pixels present in
an image. These are easier in computation and are effective in
describing both the local and global colour distribution in an
image. For huge image database, histogram comparison
saturates the discrimination. For solving such problem, the
joint histogram technique can be used. [5] As the colour
histogram doesn’t takes spatial information into account, thus
different images can have similar color histogram. This
problem becomes especially acute for large databases. To
increase the discrimination power, many improvements are
designed to consider spatial information. A simple approach
includes dividing an image into sub-parts and computing the
histogram for every sub-part separately. This division can be
simple as vertical or horizontal partition, or as complex as an
area or even object segmentation. Also, increase in the no. of
sub-parts increases the information content and also the
memory and computational time at the same time.
3. Color Correlogram
The color correlogram [6] characterizes the distributions of
pixels as well as the spatial correlation of color pairs. The 1st
and the 2nd dimension of the 3-D histogram represents the
colours of any pixel pair and the 3 dimension represents the
spatial distance. A color correlogram is in a table format, in
which the r-th entry for (i, j) is the probability of finding a pixel
of colour j at a distance r from a pixel of colour i . Let I be the
entire set of image pixels and Ib(i) the set of pixels whose
colours are b(i). For this the colour correlogram is as shown
below:
γi,j
(s)
= Pr [|p2∈ Ib(j) | | p2 – p1 |] (4)
where i, j ∈ {1, 2, 3,… M}, s∈ {1, 2, 3, …, d}, and
| p2 – p1 | mentions the distance between pixels p2 and p1.
Considering all the combinations of colour pairs, makes the
size of the colour correlogram large (O(M2d)), therefore a
simplified version of the correlogram called the color
autocorrelogram is often used. The color autocorrelogram
captures only the spatial correlation between same colors and
thus it reduces the dimension to O(Md). Compared to the other
color extraction methods, the autocorrelogram gives the better
retrieval results but at the same time it is also computational
very expensive due to its large dimensionality.
B. Texture
The texture is the visual and especially tactile quality of a
surface. It contains information about the structural
arrangement and their relation to the surrounding pixel. It is
property of virtually all surfaces including flowers, bricks,
skin, fabric, etc. There are 3 levels at which texture analysis [7]
can be discussed : On the structural level, texture is the
primitives of the image and their placement rules. On a
statistical level, a set of statistics value extracted from the
image. On the spectral level, set of coefficients in the transform
domain is texture. With the aid of above levels, the textures can
be identified but it may not agree with the human perception of
evaluating the textures. Reasons for this include semantic gap
and human perception Texture feature [8] describes spectral
features which are taken using wavelet transform, statistical
features. In the following section, we discuss Haar wavelet
Transforms and Gabor Filter Features for extraction of texture.
1. Haar wavelet Transforms
Wavelets give a multi-resolution approach for texture
classification and analysis. For a 2-dimensional image, wavelet
transform computation is also a multi resolution approach, that
applies recursive filtering and sampling. At every sub level, the
image is decomposed into 4 frequency sub-bands, LL, HH, HL,
and LH where H is the high frequency and L is the low
frequency. Let a data set X1, X2,…Xn.. contains M elements,
so there will be M/2 averages and M/2 wavelet coefficient
values. The average is stored in the 1st half of the M element
array, and the coefficient is stored in the 2nd half of the M
element array. The averages are the input in the next step in the
calculation. For a 1D Haar transform of an array of M
elements, determine the average of every pair, and find the
3. International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Volume VI, Issue IV, April 2017 | ISSN 2278-2540
www.ijltemas.in Page 79
difference between every pair of, and divide it by 2. Now fill
the 1st half with the averages, the 2nd half of the array with
coefficients. Repeat the process till a single average and a
single coefficient are determined. For a 2D Haar transform,
Compute 1D Haar wavelet decomposition for every row of the
original pixel values, then compute1D Haar wavelet
decomposition for every column of the row-transformed
pixels. RGB components are extracted from the images. Now
apply the 2D Haar transform to every colour matrix.
A feature vector is determined from every image present in the
database. Set of all the features is organized in a database
index. When similar images has to be searched with a query
image, a feature vector is again extracted from the query image
and is then matched against the feature vectors in the index.
Measure between feature representation of the query image and
feature representation of the database image is find, if it is
small, then it is considered similar. In this way, Haar wavelet
can be used for matching images from the database.
2. Gabor Filter Features
The Gabor filter [10] is used world-wide to extract features
of image, especially the texture features. It is optimal in
minimization of the joint uncertainty in frequency and in space
and is often used as an scale and orientation tunable edge and
bar/line detector. There have been many approaches which are
designed to characterize tex. of images based on Gabor filters.
A 2-dimensional Gabor function is :
g(x,y) = 1/2 x y exp[- ((x/ x)2
+ (y/ y)2
) + 2 jWx] (5)
where, σx and σy represents the standard deviations of
Gaussian envelopes along the x, y direction.
Then a list of Gabor filters is obtained by appropriate rotations
and dilations of g(x, y):
gmn(x,y) = a-m
g(x1, y1) (6)
x1= a-m
(xcosθ + ysinθ) (7)
y1= a-m
(-xsinθ + ycosθ) (8)
where a >1, θ = nπ/K, n = 0, 1, 2, 3 …, K-1, and m = 0, 1, 2 ,3
…, S-1. S and M are the no. of scales and orientations. The
scale factor a-m
is ensures that energy is independent of m.
Given an image I(x’, y’), its Gabor transform is defined as:
Wmn (x’, y’) = (x’, y’)gmn
*
(x’- x1, y’- y1) dx1dy1 (9)
where * is complex conjugate. Mean μmn and standard
deviation σmn of the |Wmn | is f = [μ00, σ00, ….μmn, σmn, Λ , μs-1k-1
,σS-1K-1 ] represents the texture feature vector of the texture
area.
C. Shape
The third feature shape can also be used for the image retrieval
process. Shape of an image may not refer to the shape of an
image but to the shape of some particular area or object in the
image. Depending on the job or application, sometimes user
requires the shape representation to be invariable to rotation,
translation and scaling. Shape features [9] of objects or areas
have been used in many CBIR systems. Unlike to colour and
text. features, shape features are generally described after
image has been segmented into parts or objects. Shape features
are categoriezed as area based and boundary based. Boundary
based uses only the outer boundary of the shape whereas
area-based shape features use entire shape area. The shape is
represented through clubbed geometric cues such as corners,
joints and polygonal areas extracted from image. Such a
clubbing may serve as a spatial layout or as a rough sketch by
additional processing. Commonly used shape feature moment
invariants and Fourier Descriptors are discussed below.
1. Moment Invariants
Moment invariants are used for the shape representation of an
image [11]. If the object S is a binary image, the central
moments of order m+n for the shape of object S are defined as:
μm,n = x-xc)m
(y-yc)n
(10)
Based on the above moments, set of invariants for rotation,
translation, and scale can be determined.
Ø1= μ2,0 + μ0,2 (11)
Ø2=(μ2,0 – μ0,2)2
+4μ2
1,1 (12)
Ø3=(μ3,0 - 3μ1,2 )2
+(μ0,3 - 3μ2,1)2
(13)
Ø4 =(μ3,0 + μ1,2 )2
+(μ0,3 - 3μ2,1)2
(14)
2. Fourier Descriptors
Fourier descriptors describes the shape of a area or object with
Fourier transform at its edge or boundary. Considering the
contour of a 2D object as a sequence of successive pixels (xi,
yi), where 0 ≤ i ≤ M-1 and M is the no. of pixels in the
boundary. The 3 types of contour representations can be
defined : centroid distance, curvature and complex coordinate
function.
The curvature C(s) at a point 'i' along the contour is change in
tangent direction of the contour, i.e.
C(s)= (15)
where θ(s) : turning function.
4. International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Volume VI, Issue IV, April 2017 | ISSN 2278-2540
www.ijltemas.in Page 80
The distance between boundary pixels and the centroid (xo, yo)
of the object is centroid distance given below:
R(s) = ((xs – xo)2
+ (ys – yo)2
)1/2
(16)
The Fourier transforms of these 3 types of contour
representations generate 3 sets of complex coefficients,
representing the shape in the frequency domain. Lower
frequency coefficients signify the general shape while higher
frequency coefficients signify shape details. The Fourier
descriptor are shown below:
For Curvature:
FK = |F1| , |F2| , | F3| .., |FM/2| (17)
For centroid distance :
fR = (18)
where Fi : ith component of Fourier transform coefficients.
Here Fourier transforms exhibit symmetry, i.e., |F-j| = |Fj|.
III. RELEVANCE FEEDBACK
The perception of human on image similarity is subjective,
semantic and job-dependent. Although methods of (CBIR)
provide challenging directions for retrieval of image, generally,
the results based on the similarities of pure features are not
inevitably semantically meaningful. Also, each type of visual
feature captures only certain aspect of image property and it
usually becomes difficult to specify how different aspects are
combined. With relevance feedback, [12] the link between
low-level and high-level features. Is established. It is a
supervised learning mechanism which is used to improve the
accuracy of CBIR systems. To improve system performance,
the main idea lies in using positive and negative examples from
the user. For a given query image, firstly the system retrieves a
set of ranked images according to a predefined similarity
measure. In the second step, the user labels the retrieved
images as relevant (positive examples) or not relevant
(negative examples). Then the system refines the retrieval
results based on the relevance feedback and presents a new list
of images to the user. Hence, the main point in relevance
feedback is incorporating both the examples to refine the query
and/or adjusting the similarity metrics.
IV. CONCLUSION
There are several methods available in CBIR for extraction of
feature In this paper, these are identified and explored to
understand the extraction and retrieval process in the CBIR
systems. From the several experiment performed it is clear that
the method based on the mixed combination of color, texture
and shape features have higher retrieval accuracy compared to
the other methods based on single feature. It is difficult to say
that one method is superior to others. To combine color
descriptors produces better retrieval rate as compared to one
color descriptors. The combination of Colour histogram and
color moments features can be combined to produce better
results. Colour histograms and coherence vector can be
combined retaining advantages of histograms with the spatial
layout. Similarly, texture feature can be combined with colour
histogram to get efficient results for image retrieval There is a
considerable increase in retrieval rate when mixed combination
of colour and texture features are used.
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