This paper presents an automated method for hand segmentation in images that make use of
signs language. For this, used an images bank that was captured by a webcam to which were applied
spatial domain methods for hand segmentation.
This paper proposed a facial expression recognition approach based on Gabor wavelet transform. Gabor wavelet filter is first used as pre-processing stage for extraction of the feature vector representation. Dimensionality of the feature vector is reduced using Principal Component Analysis and Local binary pattern (LBP) Algorithms. Experiments were carried out of The Japanese female facial expression (JAFFE) database. In all experiments conducted on JAFFE database, results obtained reveal that GW+LBP has outperformed other approaches in this paper with Average recognition rate of 90% under the same experimental setting.
This document outlines the course syllabus for Digital Image Processing (DIP). It includes 5 units covering key topics in DIP like digital image fundamentals, image enhancement, restoration and segmentation, wavelets and compression, and image representation and recognition. The syllabus allocates 45 class periods to cover these units in depth. Recommended textbooks and references for the course are also provided.
Efficient fingerprint image enhancement algorithm based on gabor filtereSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Developing 3D Viewing Model from 2D Stereo Pair with its Occlusion RatioCSCJournals
We intend to make a 3D model using a stereo pair of images by using a novel method of local matching in pixel domain for calculating horizontal disparities. We also find the occlusion ratio using the stereo pair followed by the use of The Edge Detection and Image SegmentatiON (EDISON) system, on one the images, which provides a complete toolbox for discontinuity preserving filtering, segmentation and edge detection. Instead of assigning a disparity value to each pixel, a disparity plane is assigned to each segment. We then warp the segment disparities to the original image to get our final 3D viewing Model.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
The document discusses morphological image operations and mathematical morphology. It provides examples of basic morphological operations like dilation, erosion, opening and closing. It also discusses morphological algorithms for tasks like boundary extraction, region filling, connected component extraction, skeletonization, and using morphological operations for applications like detecting foreign objects. The key concepts covered are binary morphological operations, connectivity in images, and algorithms for thinning, boundary detection, and segmentation.
Morphological image processing uses mathematical morphology tools to extract image components and describe shapes. Some key tools include binary erosion and dilation, which thin and thicken objects. Erosion shrinks objects while dilation grows them. Opening and closing are combinations of erosion and dilation that smooth contours or fill gaps. The hit-or-miss transform detects shapes by requiring matches of foreground and background pixels. Other algorithms include boundary extraction, hole filling, and thinning to find skeletons, which are medial axes of object shapes.
This paper proposed a facial expression recognition approach based on Gabor wavelet transform. Gabor wavelet filter is first used as pre-processing stage for extraction of the feature vector representation. Dimensionality of the feature vector is reduced using Principal Component Analysis and Local binary pattern (LBP) Algorithms. Experiments were carried out of The Japanese female facial expression (JAFFE) database. In all experiments conducted on JAFFE database, results obtained reveal that GW+LBP has outperformed other approaches in this paper with Average recognition rate of 90% under the same experimental setting.
This document outlines the course syllabus for Digital Image Processing (DIP). It includes 5 units covering key topics in DIP like digital image fundamentals, image enhancement, restoration and segmentation, wavelets and compression, and image representation and recognition. The syllabus allocates 45 class periods to cover these units in depth. Recommended textbooks and references for the course are also provided.
Efficient fingerprint image enhancement algorithm based on gabor filtereSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Developing 3D Viewing Model from 2D Stereo Pair with its Occlusion RatioCSCJournals
We intend to make a 3D model using a stereo pair of images by using a novel method of local matching in pixel domain for calculating horizontal disparities. We also find the occlusion ratio using the stereo pair followed by the use of The Edge Detection and Image SegmentatiON (EDISON) system, on one the images, which provides a complete toolbox for discontinuity preserving filtering, segmentation and edge detection. Instead of assigning a disparity value to each pixel, a disparity plane is assigned to each segment. We then warp the segment disparities to the original image to get our final 3D viewing Model.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
The document discusses morphological image operations and mathematical morphology. It provides examples of basic morphological operations like dilation, erosion, opening and closing. It also discusses morphological algorithms for tasks like boundary extraction, region filling, connected component extraction, skeletonization, and using morphological operations for applications like detecting foreign objects. The key concepts covered are binary morphological operations, connectivity in images, and algorithms for thinning, boundary detection, and segmentation.
Morphological image processing uses mathematical morphology tools to extract image components and describe shapes. Some key tools include binary erosion and dilation, which thin and thicken objects. Erosion shrinks objects while dilation grows them. Opening and closing are combinations of erosion and dilation that smooth contours or fill gaps. The hit-or-miss transform detects shapes by requiring matches of foreground and background pixels. Other algorithms include boundary extraction, hole filling, and thinning to find skeletons, which are medial axes of object shapes.
This document provides an overview of mathematical morphology and its applications in image processing. Some key points:
- Mathematical morphology uses concepts from set theory and uses structuring elements to probe and modify binary and grayscale images.
- Basic morphological operations include erosion, dilation, opening, closing, hit-or-miss transformation, thinning, thickening, and skeletonization.
- Erosion shrinks objects and removes small details while dilation expands objects and fills small holes. Opening and closing combine these to smooth contours or fuse breaks.
- Morphological operations have many applications including boundary extraction, region filling, component labeling, convex hulls, pruning, and more. Grayscale images extend these concepts using minimum/maximum
This paper presents an improved edge detection algorithm for facial and remotely sensed images using
vector order statistics. The developed algorithm processes coloured images directly without been converted
to grey scale. A number of the existing algorithms converts the coloured images into grey scale before
detection of edges. But this process leads to inaccurate precision of recognized edges, thus producing false
and broken edges in the output edge map. Facial and remotely sensed images consist of curved edge lines
which have to be detected continuously to prevent broken edges. In order to deal with this, a collection of
pixel approach is introduced with a view to minimizing the false and broken edges that exists in the
generated output edge map of facial and remotely sensed images.
This document discusses several topics in image enhancement and processing including:
1. Spatial filtering which involves applying a weighted mask over an image to replace pixel values.
2. Logarithmic transformation which expands darker pixel values more than brighter ones for enhancement.
3. Thresholding, logarithmic transformation, negative transformation, contrast stretching, and grey level slicing as common nonlinear image transformations.
4. Weighted average filtering which applies different coefficients to pixels to give more importance to some over others.
5. High boost filters and unsharp masking as types of high pass sharpening filters used to highlight fine image details.
At the end of this lecture, you should be able to;
describe the importance of morphological features in an image.
describe the operation of erosion, dilation, open and close operations.
identify the practical advantage of the morphological operations.
apply morphological operations for problem solving.
The document discusses various morphological image processing techniques including binary morphology, grayscale morphology, dilation, erosion, opening, closing, boundary extraction, region filling, connected components, hit-or-miss, thinning, thickening, and skeletonization. Morphological operations can be used for tasks like edge detection, noise removal, image enhancement, and image segmentation. The key morphological operations of dilation and erosion expand and shrink binary images using a structuring element, while opening and closing combine these operations to remove noise or fill holes.
Performance of Efficient Closed-Form Solution to Comprehensive Frontier Exposureiosrjce
This document discusses boundary detection techniques for images. It proposes a generalized boundary detection method (Gb) that combines low-level and mid-level image representations in a single eigenvalue problem to detect boundaries. Gb achieves state-of-the-art results at low computational cost. Soft segmentation and contour grouping methods are also introduced to further improve boundary detection accuracy with minimal extra computation. The document presents outputs of Gb on sample images and concludes that Gb effectively detects boundaries in a principled manner by jointly resolving constraints from multiple image interpretation layers in closed form.
B. SC CSIT Computer Graphics Unit 3 By Tekendra Nath YogiTekendra Nath Yogi
This document discusses various methods for 3D object representation in computer graphics. It covers surface modeling techniques like polygon meshes, parametric cubic curves, and quadratic surfaces. It also discusses solid modeling representations such as sweep, boundary, and spatial partitioning. Additionally, it provides details on polygon mesh data structures, plane equations, quadric surfaces, and parametric cubic curves. Specifically, it explains how to define curves using parametric cubic functions and calculate coefficients for natural cubic splines.
B. SC CSIT Computer Graphics Unit 4 By Tekendra Nath YogiTekendra Nath Yogi
The document discusses various techniques for visible surface determination and surface rendering in 3D graphics. It covers algorithms like z-buffer, list priority, and scan line algorithms for visible surface detection. It also discusses illumination models, surface shading methods like Gouraud and Phong shading, and provides pseudocode examples for image space and object space visible surface determination methods. Specific algorithms covered in more detail include the back face detection, z-buffer, list priority, and scan line algorithms.
This document provides an overview of various digital image processing techniques including morphological transformations, geometric transformations, image gradients, Canny edge detection, image thresholding, and a practical demo assignment. It discusses the basic concepts and algorithms for each technique and provides examples code. The document is presented as part of a practical course on digital image processing.
This document appears to be an exam for a course on image processing. It contains 20 multiple choice questions testing concepts related to image processing techniques. Some of the concepts addressed include image transformations, filtering, restoration, and color space conversions. The questions cover topics such as piecewise linear transformations, monotonic functions, histogram processing methods, distance metrics, and stages of image processing like acquisition and enhancement.
Mathematical morphology is a framework for image analysis using set theory operations. It is used for tasks like noise filtering, shape analysis, and segmentation. Basic operations include erosion, dilation, opening, and closing using a structuring element. Erosion shrinks objects while dilation expands them. Opening eliminates small objects and closing fills small holes. Together these operations can filter images while preserving overall shapes. Morphological operations also enable extracting object boundaries, thinning images to skeletons, and finding connected components.
The document discusses image segmentation techniques. It defines image segmentation as partitioning a digital image into multiple segments or regions that are similar in characteristics such as color or texture. The main goal of image segmentation is to simplify an image into meaningful parts for analysis. Common techniques discussed include thresholding, clustering, edge detection, region growing, and neural networks. Thresholding uses threshold values to separate pixels into multiple classes or objects. Clustering groups similar image pixels together while edge detection finds boundaries between objects. The document also provides an example of the split and merge segmentation method.
This document provides an overview of mathematical morphology and its applications to image processing. Some key points:
- Mathematical morphology uses concepts from set theory and uses structuring elements to probe and extract image properties. It provides tools for tasks like noise removal, thinning, and shape analysis.
- Basic operations include erosion, dilation, opening, and closing. Erosion shrinks objects while dilation expands them. Opening and closing combine these to smooth contours or fill gaps.
- Hit-or-miss transforms allow detecting specific shapes. Skeletonization reduces objects to 1-pixel wide representations.
- Morphological operations can be applied to binary or grayscale images. Structuring elements are used to specify the neighborhood of pixels
Morphology fundamentals consist of erosion and dilation, which are basic morphological operations. Erosion removes pixels from object boundaries, shrinking object sizes and enlarging holes. Dilation adds pixels to boundaries, enlarging object sizes and shrinking holes. Both operations use a structuring element to determine how many pixels are added or removed. Erosion compares the structuring element to the image, removing pixels where it is not contained. Dilation compares overlaps, adding pixels where the structuring element and image overlap by at least one element.
1) The document describes generating 3D models of a full ball and deflated ball using photogrammetry. Photos were taken with a Sony Alpha 6300 camera and processed in Agisoft Photoscan.
2) Dense point clouds, mesh models, and textured 3D models were successfully generated but had some distortion at the bottom. More overlapping photos from different angles were needed to fully capture the spherical objects.
3) CloudCompare software aligned and compared the two point clouds, finding a mean deformation of 8.395 mm between the full and deflated balls. The alignment and scale of point clouds affected the accuracy of deformation measurements.
Multimedia content based retrieval in digital librariesMazin Alwaaly
This document provides an overview of content-based image retrieval (CBIR) systems. It discusses early CBIR systems and provides a case study of C-BIRD, a CBIR system that uses features like color histograms, color layout, texture analysis, and object models to perform image searches. It also covers quantifying search results, key technologies in current CBIR systems such as robust image features, relevance feedback, and visual concept search, and the role of users in interactive CBIR systems.
This document summarizes key concepts in morphological image processing including dilation, erosion, opening, closing, and hit-or-miss transformations. Morphological operations manipulate image shapes and structures using structuring elements based on set theory operations. Dilation adds pixels to the boundaries of objects in an image, while erosion removes pixels on object boundaries. Opening can remove noise and smooth object contours, while closing can fill in small holes and fill gaps in object shapes. Hit-or-miss transformations are used to detect specific patterns of on and off pixels. These operations form the basis for morphological algorithms like boundary extraction.
This document discusses different techniques for image segmentation. It begins by defining image segmentation as dividing an image into regions based on similarity and differences between adjacent regions. The main approaches discussed are discontinuity-based segmentation, which looks for sudden changes in pixel intensity (edges), and similarity-based segmentation, which groups similar pixels into regions. The document then examines various methods for detecting edges, linking edges, thresholding, and region-based segmentation using techniques like region growing and splitting/merging.
Divide the examined window into cells (e.g. 16x16 pixels for each cell).
2- For each pixel in a cell, compare the pixel to each of its 8 neighbors (on its left-top, leftmiddle,
left-bottom, right-top, etc.). Follow the pixels along a circle, i.e. clockwise or counterclockwise.
3- Where the center pixel's value is greater than the neighbor's value, write "1". Otherwise,
write "0". This gives an 8-digit binary number (which is usually converted to decimal for
convenience).
4- Compute the histogram, over the cell, of the frequency of each "number" occurring (i.e.,
each combination of which pixels are smaller and which are greater than the center).
Face Detection for identification of people in Images of Internetijceronline
One method for searching the internet faces in images is proposed by using digital processing topological with descriptors. Location in real time with the development of a database that stores addresses of internet downloaded images, in which the search is done by text, but by finding facial image, is achieved. Face recognition in images of Internet has proved to be a difficult task, because the images vary considerably depending on viewpoint, illumination, expression, pose, accessories, etc. The descriptors for general information: containing low-level descriptors. Developments on face recognition systems have improved significantly since the first system; image analysis is a topic on which much emphasis is being given in order to identify parameters, visual features in the image that provide environment data that it is represented in the image, but without the intervention of a person. In this project raises its realization using the method of viola and jones as face descriptor. We can distinguish even different parts of the face such as eyes, eyebrows, nose and mouth.One method for searching faces in image taken from internet intends to use digital processing using topological descriptors. It is located the face in real time.
The document discusses hand gesture recognition including hand-forearm segmentation, palm-finger segmentation, and gesture recognition. It describes algorithms for identifying the hand region, separating the palm and fingers, and recognizing gestures based on features like finger positions. Logistic regression is used to train classifiers to identify gestures belonging to different classes and subclasses based on the number and orientation of fingers. Applications mentioned include sign language, robot control, gaming, and controlling smart TVs.
This document discusses a study on using different machine learning classifiers for classification and regression problems. It first provides a brief description of linear regression, logistic regression, neural networks, and support vector machines. It then discusses using these classifiers on classification and regression data. For classification data consisting of hand gesture images, logistic regression achieved 87.89% accuracy, while support vector machines achieved 90% accuracy with a linear kernel. Neural networks generally performed best by training more complex models without overfitting. Overall, the study evaluated the performance of different machine learning algorithms on sample datasets.
This document provides an overview of mathematical morphology and its applications in image processing. Some key points:
- Mathematical morphology uses concepts from set theory and uses structuring elements to probe and modify binary and grayscale images.
- Basic morphological operations include erosion, dilation, opening, closing, hit-or-miss transformation, thinning, thickening, and skeletonization.
- Erosion shrinks objects and removes small details while dilation expands objects and fills small holes. Opening and closing combine these to smooth contours or fuse breaks.
- Morphological operations have many applications including boundary extraction, region filling, component labeling, convex hulls, pruning, and more. Grayscale images extend these concepts using minimum/maximum
This paper presents an improved edge detection algorithm for facial and remotely sensed images using
vector order statistics. The developed algorithm processes coloured images directly without been converted
to grey scale. A number of the existing algorithms converts the coloured images into grey scale before
detection of edges. But this process leads to inaccurate precision of recognized edges, thus producing false
and broken edges in the output edge map. Facial and remotely sensed images consist of curved edge lines
which have to be detected continuously to prevent broken edges. In order to deal with this, a collection of
pixel approach is introduced with a view to minimizing the false and broken edges that exists in the
generated output edge map of facial and remotely sensed images.
This document discusses several topics in image enhancement and processing including:
1. Spatial filtering which involves applying a weighted mask over an image to replace pixel values.
2. Logarithmic transformation which expands darker pixel values more than brighter ones for enhancement.
3. Thresholding, logarithmic transformation, negative transformation, contrast stretching, and grey level slicing as common nonlinear image transformations.
4. Weighted average filtering which applies different coefficients to pixels to give more importance to some over others.
5. High boost filters and unsharp masking as types of high pass sharpening filters used to highlight fine image details.
At the end of this lecture, you should be able to;
describe the importance of morphological features in an image.
describe the operation of erosion, dilation, open and close operations.
identify the practical advantage of the morphological operations.
apply morphological operations for problem solving.
The document discusses various morphological image processing techniques including binary morphology, grayscale morphology, dilation, erosion, opening, closing, boundary extraction, region filling, connected components, hit-or-miss, thinning, thickening, and skeletonization. Morphological operations can be used for tasks like edge detection, noise removal, image enhancement, and image segmentation. The key morphological operations of dilation and erosion expand and shrink binary images using a structuring element, while opening and closing combine these operations to remove noise or fill holes.
Performance of Efficient Closed-Form Solution to Comprehensive Frontier Exposureiosrjce
This document discusses boundary detection techniques for images. It proposes a generalized boundary detection method (Gb) that combines low-level and mid-level image representations in a single eigenvalue problem to detect boundaries. Gb achieves state-of-the-art results at low computational cost. Soft segmentation and contour grouping methods are also introduced to further improve boundary detection accuracy with minimal extra computation. The document presents outputs of Gb on sample images and concludes that Gb effectively detects boundaries in a principled manner by jointly resolving constraints from multiple image interpretation layers in closed form.
B. SC CSIT Computer Graphics Unit 3 By Tekendra Nath YogiTekendra Nath Yogi
This document discusses various methods for 3D object representation in computer graphics. It covers surface modeling techniques like polygon meshes, parametric cubic curves, and quadratic surfaces. It also discusses solid modeling representations such as sweep, boundary, and spatial partitioning. Additionally, it provides details on polygon mesh data structures, plane equations, quadric surfaces, and parametric cubic curves. Specifically, it explains how to define curves using parametric cubic functions and calculate coefficients for natural cubic splines.
B. SC CSIT Computer Graphics Unit 4 By Tekendra Nath YogiTekendra Nath Yogi
The document discusses various techniques for visible surface determination and surface rendering in 3D graphics. It covers algorithms like z-buffer, list priority, and scan line algorithms for visible surface detection. It also discusses illumination models, surface shading methods like Gouraud and Phong shading, and provides pseudocode examples for image space and object space visible surface determination methods. Specific algorithms covered in more detail include the back face detection, z-buffer, list priority, and scan line algorithms.
This document provides an overview of various digital image processing techniques including morphological transformations, geometric transformations, image gradients, Canny edge detection, image thresholding, and a practical demo assignment. It discusses the basic concepts and algorithms for each technique and provides examples code. The document is presented as part of a practical course on digital image processing.
This document appears to be an exam for a course on image processing. It contains 20 multiple choice questions testing concepts related to image processing techniques. Some of the concepts addressed include image transformations, filtering, restoration, and color space conversions. The questions cover topics such as piecewise linear transformations, monotonic functions, histogram processing methods, distance metrics, and stages of image processing like acquisition and enhancement.
Mathematical morphology is a framework for image analysis using set theory operations. It is used for tasks like noise filtering, shape analysis, and segmentation. Basic operations include erosion, dilation, opening, and closing using a structuring element. Erosion shrinks objects while dilation expands them. Opening eliminates small objects and closing fills small holes. Together these operations can filter images while preserving overall shapes. Morphological operations also enable extracting object boundaries, thinning images to skeletons, and finding connected components.
The document discusses image segmentation techniques. It defines image segmentation as partitioning a digital image into multiple segments or regions that are similar in characteristics such as color or texture. The main goal of image segmentation is to simplify an image into meaningful parts for analysis. Common techniques discussed include thresholding, clustering, edge detection, region growing, and neural networks. Thresholding uses threshold values to separate pixels into multiple classes or objects. Clustering groups similar image pixels together while edge detection finds boundaries between objects. The document also provides an example of the split and merge segmentation method.
This document provides an overview of mathematical morphology and its applications to image processing. Some key points:
- Mathematical morphology uses concepts from set theory and uses structuring elements to probe and extract image properties. It provides tools for tasks like noise removal, thinning, and shape analysis.
- Basic operations include erosion, dilation, opening, and closing. Erosion shrinks objects while dilation expands them. Opening and closing combine these to smooth contours or fill gaps.
- Hit-or-miss transforms allow detecting specific shapes. Skeletonization reduces objects to 1-pixel wide representations.
- Morphological operations can be applied to binary or grayscale images. Structuring elements are used to specify the neighborhood of pixels
Morphology fundamentals consist of erosion and dilation, which are basic morphological operations. Erosion removes pixels from object boundaries, shrinking object sizes and enlarging holes. Dilation adds pixels to boundaries, enlarging object sizes and shrinking holes. Both operations use a structuring element to determine how many pixels are added or removed. Erosion compares the structuring element to the image, removing pixels where it is not contained. Dilation compares overlaps, adding pixels where the structuring element and image overlap by at least one element.
1) The document describes generating 3D models of a full ball and deflated ball using photogrammetry. Photos were taken with a Sony Alpha 6300 camera and processed in Agisoft Photoscan.
2) Dense point clouds, mesh models, and textured 3D models were successfully generated but had some distortion at the bottom. More overlapping photos from different angles were needed to fully capture the spherical objects.
3) CloudCompare software aligned and compared the two point clouds, finding a mean deformation of 8.395 mm between the full and deflated balls. The alignment and scale of point clouds affected the accuracy of deformation measurements.
Multimedia content based retrieval in digital librariesMazin Alwaaly
This document provides an overview of content-based image retrieval (CBIR) systems. It discusses early CBIR systems and provides a case study of C-BIRD, a CBIR system that uses features like color histograms, color layout, texture analysis, and object models to perform image searches. It also covers quantifying search results, key technologies in current CBIR systems such as robust image features, relevance feedback, and visual concept search, and the role of users in interactive CBIR systems.
This document summarizes key concepts in morphological image processing including dilation, erosion, opening, closing, and hit-or-miss transformations. Morphological operations manipulate image shapes and structures using structuring elements based on set theory operations. Dilation adds pixels to the boundaries of objects in an image, while erosion removes pixels on object boundaries. Opening can remove noise and smooth object contours, while closing can fill in small holes and fill gaps in object shapes. Hit-or-miss transformations are used to detect specific patterns of on and off pixels. These operations form the basis for morphological algorithms like boundary extraction.
This document discusses different techniques for image segmentation. It begins by defining image segmentation as dividing an image into regions based on similarity and differences between adjacent regions. The main approaches discussed are discontinuity-based segmentation, which looks for sudden changes in pixel intensity (edges), and similarity-based segmentation, which groups similar pixels into regions. The document then examines various methods for detecting edges, linking edges, thresholding, and region-based segmentation using techniques like region growing and splitting/merging.
Divide the examined window into cells (e.g. 16x16 pixels for each cell).
2- For each pixel in a cell, compare the pixel to each of its 8 neighbors (on its left-top, leftmiddle,
left-bottom, right-top, etc.). Follow the pixels along a circle, i.e. clockwise or counterclockwise.
3- Where the center pixel's value is greater than the neighbor's value, write "1". Otherwise,
write "0". This gives an 8-digit binary number (which is usually converted to decimal for
convenience).
4- Compute the histogram, over the cell, of the frequency of each "number" occurring (i.e.,
each combination of which pixels are smaller and which are greater than the center).
Face Detection for identification of people in Images of Internetijceronline
One method for searching the internet faces in images is proposed by using digital processing topological with descriptors. Location in real time with the development of a database that stores addresses of internet downloaded images, in which the search is done by text, but by finding facial image, is achieved. Face recognition in images of Internet has proved to be a difficult task, because the images vary considerably depending on viewpoint, illumination, expression, pose, accessories, etc. The descriptors for general information: containing low-level descriptors. Developments on face recognition systems have improved significantly since the first system; image analysis is a topic on which much emphasis is being given in order to identify parameters, visual features in the image that provide environment data that it is represented in the image, but without the intervention of a person. In this project raises its realization using the method of viola and jones as face descriptor. We can distinguish even different parts of the face such as eyes, eyebrows, nose and mouth.One method for searching faces in image taken from internet intends to use digital processing using topological descriptors. It is located the face in real time.
The document discusses hand gesture recognition including hand-forearm segmentation, palm-finger segmentation, and gesture recognition. It describes algorithms for identifying the hand region, separating the palm and fingers, and recognizing gestures based on features like finger positions. Logistic regression is used to train classifiers to identify gestures belonging to different classes and subclasses based on the number and orientation of fingers. Applications mentioned include sign language, robot control, gaming, and controlling smart TVs.
This document discusses a study on using different machine learning classifiers for classification and regression problems. It first provides a brief description of linear regression, logistic regression, neural networks, and support vector machines. It then discusses using these classifiers on classification and regression data. For classification data consisting of hand gesture images, logistic regression achieved 87.89% accuracy, while support vector machines achieved 90% accuracy with a linear kernel. Neural networks generally performed best by training more complex models without overfitting. Overall, the study evaluated the performance of different machine learning algorithms on sample datasets.
Hand gesture recognition system has received great attention in the recent few years because of its manifoldness applications and the ability to interact with machine efficiently through human computer interaction. In this work Hand segmentation using color models is introduced for obtaining hand gestures or detecting user’s hand by color segmentation technique for faster, better, robust, accurate and real-time applications. There are many such color models available for human hand and human skin detection with relative advantages and disadvantages in the field of Image Processing. For the purpose of hand Segmentation mix model approach has been adopted for best results. For detection of Hand from an image. The proposed approach is found to be accurate and effective for multiple conditions
The document describes image processing techniques using MATLAB. It provides 12 chapters covering topics like color maps, image addition, image complement, image histograms, image filtering, edge detection, and converting between image formats. Code examples and output are provided for each chapter to demonstrate the techniques.
This document discusses a student project involving image processing using MATLAB and Arduino. It lists the group members and describes using a webcam mounted on a robot for noise removal from live images. It discusses the theory of image acquisition, processing, data communication, and the Matlab and Arduino programs. It also provides information on Arduino boards, sensors, actuators, and the ULN2803 motor driver. It describes various video processing applications and techniques like tracking, motion detection, background subtraction, and optical flow.
The document discusses implementing the watershed algorithm for image segmentation using MATLAB. It begins with an overview of the watershed algorithm which uses region growing to segment images based on gradients. It then discusses image segmentation goals and different categories of segmentation algorithms including discontinuity, similarity, thresholding and region-based approaches. The document outlines steps to be taken which include preprocessing images, implementing the watershed algorithm, and analyzing results to see the difference in segmented images. It expects watershed processing to produce segmented regions from a test image.
Color based image processing , tracking and automation using matlabKamal Pradhan
Image processing is a form of signal processing in which the input is an image, such as a photograph or video frame. The output of image processing may be either an image or, a set of characteristics or parameters related to the image. Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal-processing techniques to it. This project aims at processing the real time images captured by a Webcam for motion detection and Color Recognition and system automation using MATLAB programming.
In color based image processing we work with colors instead of object. Color provides powerful information for object recognition. A simple and effective recognition scheme is to represent and match images on the basis of color histograms.
Tracking refers to detection of the path of the color once the color based processing is done the color becomes the object to be tracked this can be very helpful in security purposes.
Automation refers to an automated system is any system that does not require human intervention. In this project I’ve automated the mouse that work with our gesture and do the desired tasks.
The document discusses various techniques for image segmentation. It begins by defining image segmentation as dividing an image into constituent regions or objects. It then describes several segmentation methods including those based on discontinuity, similarity, grey scale, texture, motion, depth, edge detection, region growing, and thresholding. Thresholding techniques include global thresholding of the image histogram as well as adaptive thresholding which divides an image into sub-images for thresholding. The goal of segmentation is to extract objects of interest from an image.
This MATLAB section of source code covers MATLAB based projects.
Download free source code viz. FIR,IIR,scrambler,interleaver,FFT,convolution,correlation,interpolation,decimation,CRC,impairments,data type conversions and more.
RS encoder,convolutional encoder,viterbi decoder,OFDM,OFDMA,MIMO is also covered.WiMAX,WLAN,LTE source codes are also provided.
This document provides an overview and examples of using MATLAB. It introduces MATLAB, describing its origins and applications in fields like aerospace, robotics, and more. It then covers various topics within MATLAB like image processing, reading and writing images, converting images to binary and grayscales, plotting functions, and using GUI tools. Examples of code are provided for tasks like reading images, filtering noise, and capturing video from a webcam. The document also lists some common file extensions used in MATLAB and describes serial communication.
The document provides an overview of basic image processing concepts and techniques using MATLAB, including:
- Reading and displaying images
- Performing operations on image matrices like dilation, erosion, and thresholding
- Segmenting images using global and local thresholding methods
- Identifying and labeling connected components
- Extracting properties of connected components using regionprops
- Performing tasks like edge detection and noise removal
Code examples and explanations are provided for key functions like imread, imshow, imdilate, imerode, im2bw, regionprops, and edge.
This document provides an introduction to image segmentation. It discusses how image segmentation partitions an image into meaningful regions based on measurements like greyscale, color, texture, depth, or motion. Segmentation is often an initial step in image understanding and has applications in identifying objects, guiding robots, and video compression. The document describes thresholding and clustering as two common segmentation techniques and provides examples of segmentation based on greyscale, texture, motion, depth, and optical flow. It also discusses region-growing, edge-based, and active contour model approaches to segmentation.
An Experimental Investigation on Mode-II Fracture of Light Weight Pumice Aggr...IJMER
Shear strength is a property of major significance for wide range of civil engineering
materials and structures. Shear and punching shear failures particularly in deep beams in corbels and in
concrete flat slabs are considered to be more critical and catastrophic than other types of failures. To study
such failures the past literature suggests best suited geometry as Double Centered Notched (DCN)
specimen geometry proposed by Sri Prakash Desai and Sri Bhaskar Desai. In the present scenario light
weight aggregate has been the subject of extensive research which affects the strength properties of cement
concrete. Light weight aggregate concrete has become more popular in recent advancements owing to the
tremendous advantages it offers over the conventional concrete but at the same time light in weight and
strong enough to be used for structural purposes. In this present experimental investigation an attempt is
made to study the Mode-II fracture properties of natural light weight aggregate concrete, such as pumice
aggregate (which is volcanic based and imported from Turkey) concrete. By varying the percentage of light
weight pumice aggregate in concrete replacing the conventional granite aggregate in percentages like 0%,
25%, 50%, 75% and 100% by volume of concrete, the mode-II fracture property such as in plane shear
strength is studied. Finally an analysis is carried out regarding Mode-II fracture properties of pumice
concrete and it is concluded that shear strength is decreased continuously with increase in percentage of
pumice.
Stability of the Equilibrium Position of the Centre of Mass of an Inextensibl...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Energy Audit is the systematic process for finding out the energy conservation
opportunities in industrial processes. The project carried out studies on various energy conservation
measures application in areas like lighting, motors, compressors, transformer, ventilation system etc.
In this investigation, studied the technical aspects of the various measures along with its cost benefit
analysis.
Investigation found that major areas of energy conservation are-
1. Energy efficient lighting schemes.
2. Use of electronic ballast instead of copper ballast.
3. Use of wind ventilators for ventilation.
4. Use of VFD for compressor.
5. Transparent roofing sheets to reduce energy consumption.
So Energy Audit is the only perfect & analyzed way of meeting the Industrial Energy Conservation.
Fuzzy soft set is one of the recent topics developed for dealing with the uncertainties present
in most of our real life situations. The parameterization tool of soft set theory enhances the flexibility of
its application. In this paper, we have studied membership grade, power set,
-cut set , strong fuzzy
-
cut set ,some standard operation fuzzy soft set, degree of subset hood and proposed some results with
examples.
Simcoe website presentation version 2 dec 16Miles McDonald
Simcoe Renewable Energy is a Canadian company that secures investment for solar energy projects including microgrids and utility-scale solar plants. The document outlines Simcoe's microgrid project for the Simcoe area, which would provide reliable solar-generated electricity. Key benefits of the microgrid include no upfront capital costs, an established price per kWh, reliability independent of the wider electricity grid, and energy cost savings of 20% compared to current costs. Simcoe handles project development, financing, construction, and long-term operation and maintenance through a power purchase agreement with the client.
A Novel Approach To Answer Continuous Aggregation Queries Using Data Aggregat...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
The document defines and studies the properties of g#p-continuous maps between topological spaces. It is shown that:
1. Every pre-continuous, α-continuous, gα-continuous and continuous map is g#p-continuous.
2. The class of g#p-continuous maps properly contains and is properly contained in other classes of generalized continuous maps.
3. g#p-continuity is independent of other properties like semi-continuity and β-continuity.
4. The composition of two g#p-continuous maps need not be g#p-continuous.
This document describes the design of remote cooling systems for diesel generator sets. It discusses three types of remote cooling systems: remote radiators, remote radiators with auxiliary pumps, and remote radiators with hot wells. For each system, it provides details on components, design considerations, and design procedures. The key points are that remote cooling systems allow radiators to be placed separately from the generator set but require additional components like pumps and controls. The design must ensure cooling needs are met within static and friction head limits of the engine.
Face Detection and Recognition Using Back Propagation Neural Network and Four...sipij
This document presents a face detection and recognition system using Back Propagation Neural Network (BPNN) and Fourier Gabor filters. The system first uses HSV color space to detect skin regions and extract faces. Fourier Gabor filters with 8 orientations and 5 resolutions are then applied to extract features, generating a feature vector. This vector is fed into a BPNN for classification. Experiments on the XM2VTSDB database showed the proposed method achieved good recognition results with some robustness to variations in expression and pose.
Hybrid Technique for Copy-Move Forgery Detection Using L*A*B* Color Space IJEEE
Copy-move forgery is applied on an image to hide a region or an object. Most of the detection techniques either use transform domain or spatial domain information to detect the forgery. This paper presents a hybrid method to detect the forgery making use of both the domains i.e. transform domain in whichSVD is used to extract the useful information from image and spatial domain in which L*a*b* color space is used. Here block based approach and lexicographical sorting is used to group matching feature vectors. Obtained experimental results demonstrate that proposed method efficiently detects copy-move forgery even when post-processing operations like blurring, noise contamination, and severe lossy compression are applied.
Image enhancement technique plays vital role in improving the quality of the image. Enhancement
technique basically enhances the foreground information and retains the background and improve the
overall contrast of an image. In some case the background of an image hides the structural information of
an image. This paper proposes an algorithm which enhances the foreground image and the background
part separately and stretch the contrast of an image at inter-object level and intra-object level and then
combines it to an enhanced image. The results are compared with various classical methods using image
quality measures
Hand and wrist localization approach: sign language recognition Sana Fakhfakh
This document proposes a new method for hand detection and wrist localization to achieve automatic recognition of Arabic sign language gestures without clothing or background conditions. The method involves:
1) Using marker-controlled watershed segmentation to localize the hand region.
2) Rotating the hand region vertically, dividing it into sections, and detecting the wrist position as the first line with minimum white pixels in the hand region and maximum black pixels in the background region, focusing the search in the lower sections to avoid detecting fingers.
3) Extracting shape-based features like geometric moments and Zernike moments from the localized hand region to recognize Arabic digit sign gestures for sign language interaction.
A comparative study on content based image retrieval methodsIJLT EMAS
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.
Face Recognition Using Neural Network Based Fourier Gabor Filters & Random Pr...CSCJournals
Face detection and recognition has many applications in a variety of fields such as authentication, security, video surveillance and human interaction systems. In this paper, we present a neural network system for face recognition. Feature vector based on Fourier Gabor filters is used as input of our classifier, which is a Back Propagation Neural Network (BPNN). The input vector of the network will have large dimension, to reduce its feature subspace we investigate the use of the Random Projection as method of dimensionality reduction. Theory and experiment indicates the robustness of our solution.
This document proposes a method for change detection in images that combines Change Vector Analysis, K-Means clustering, Otsu thresholding, and mathematical morphology. It involves detecting intensity changes using CVA, segmenting the difference image using K-Means, calculating a threshold with Otsu's method, applying the threshold and morphological operations, and comparing results to other change detection techniques. Experimental results on medical and other images show the proposed method achieves satisfactory change detection with fewer errors compared to other methods.
This document discusses techniques for image segmentation and edge detection. It proposes a generalized boundary detection method called Gb that combines low-level and mid-level image representations in a single eigenvalue problem to detect boundaries. Gb achieves state-of-the-art results at low computational cost. Soft segmentation is also introduced to improve boundary detection accuracy with minimal extra computation. Common methods for edge detection are described, including gradient-based, texture-based, and projection profile-based approaches. Improved Harris and corner detection algorithms are presented to more accurately detect edges and corners. The output of Gb using soft segmentations as input is shown to correlate well with occlusions and whole object boundaries while capturing general boundaries.
Edge detection of herbal plants is a set of mathematical methods which aim at identifying points in a digital image at which the image brightness changes sharply and has discontinuities. They are defined as the set of curved line segments termed edges. Effective edge detection for microscopic image of herbal plant is proposed through this paper which compares the edge detected images and then performs further segmentation. Comparison between Sobel operator, Prewitt, Canny and Robert cross operators is performed. Our method after efficient edge detection performs Gabor filter and K-means clustering to procure a better image. It is then subjected to further segmentation. Experimental methods in our proposed algorithm show that our method achieves a better edge detection as compared to other edge detector operators. Our proposed algorithm provides the maximum PSNR value of 43.684 amongst the other commercial edge detection operators.
A digital image forensic approach to detect whether
an image has been seam carved or not is investigated herein.
Seam carving is a content-aware image retargeting technique
which preserves the semantically important content of an image
while resizing it. The same technique, however, can be used
for malicious tampering of an image. 18 energy, seam, and
noise related features defined by Ryu [1] are produced using
Sobel’s [2] gradient filter and Rubinstein’s [3] forward energy
criterion enhanced with image gradients. An extreme gradient
boosting classifier [4] is trained to make the final decision.
Experimental results show that the proposed approach improves
the detection accuracy from 5 to 10% for seam carved images
with different scaling ratios when compared with other state-ofthe-
art methods.
The document discusses using machine learning algorithms like Support Vector Machines (SVM) for classification and Support Vector Regression (SVR) for regression on facial image data. Dimensionality reduction using Locality Preserving Projections is also discussed to reduce computational requirements. SVM classification of gender on a subset of 3000 images achieved over 99% accuracy. SVR is noted to better handle outliers in facial data compared to basic linear regression due to minimizing slope. The goal is to classify gender and regress age from a set of facial images.
In this project, we proposed a Content Based Image Retrieval (CBIR) system which is used to retrieve a
relevant image from an outsized database. Textile images showed the way for the development of CBIR. It
establishes the efficient combination of color, shape and texture features. Here the textile image is given as
dataset. The images in database are loaded. The resultant image is given as input to feature extraction
technique which is transformation of input image into a set of features such as color, texture and shape.
The texture feature of an image is taken out by using Gray level co-occurrence matrix (GLCM). The color
feature of an image is obtained by HSI color space. The shape feature of an image is extorted by sobel
technique. These algorithms are used to calculate the similarity between extracted features. These features
are combined effectively so that the retrieval accuracy and recall rate is enhanced. The classification
techniques such as Support Vector Machine (SVM) are used to classify the features of a query image by
splitting the group such as color, shape and texture. Finally, the relevant images are retrieved from a large
database and hence the efficiency of an image is plotted.The software used is MATLAB 7.10 (matrix
laboratory) which is built software applications
This document summarizes and reviews several techniques for image mining, including feature extraction, image clustering, and object recognition algorithms. It discusses color, texture, and edge feature extraction techniques and evaluates their precision and recall. It also describes the block truncation algorithm for image recognition and the cascade feature extraction approach. The key techniques - color moments, block truncation coding, and cascade classifiers - are evaluated based on experimental recall and precision results. Overall, the document provides an overview of different image mining techniques and evaluates their effectiveness.
Edge detection algorithm based on quantum superposition principle and photons...IJECEIAES
The detection of object edges in images is a crucial step employed in a vast amount of computer vision applications, for which a series of different algorithms has been developed in the last decades. This paper proposes a new edge detection method based on quantum information, which is achieved in two main steps: (i) an image enhancement stage that employs the quantum superposition law and (ii) an edge detection stage based on the probability of photon arrival to the camera sensor. The proposed method has been tested on synthetic and real images devoted to agriculture applications, where Fram & Deutsh criterion has been adopted to evaluate its performance. The results show that the proposed method gives better results in terms of detection quality and computation time compared to classical edge detection algorithms such as Sobel, Kayyali, Canny and a more recent algorithm based on Shannon entropy.
A Novel 2D Feature Extraction Method for Fingerprints Using Minutiae Points a...IJECEIAES
The field of biometrics has evolved tremendously for over the last century. Yet scientists are still continuing to come up with precise and efficient algorithms to facilitate automatic fingerprint recognition systems. Like other applications, an efficient feature extraction method plays an important role in fingerprint based recognition systems. This paper proposes a novel feature extraction method using minutiae points of a fingerprint image and their intersections. In this method, initially, it calculates the ridge ends and ridge bifurcations of each fingerprint image. And then, it estimates the minutiae points for the intersection of each ridge end and ridge bifurcation. In the experimental evaluation, we tested the extracted features of our proposed model using a support vector machine (SVM) classifier and experimental results show that the proposed method can accurately classify different fingerprint images.
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.
IRJET-Real Time Hand Gesture Recognition using Finger TipsIRJET Journal
This document presents a real-time method for hand gesture recognition using finger tips. The method first extracts the hand region from images using skin color thresholding. It then segments the finger-palm region and locates the palm center and finger tips. The number of detected finger tips and angles between finger tips and palm center are used by a rule-based classifier to predict the hand gesture label in real-time. The method was tested on five static gestures and achieved over 85% accuracy on average. Future work could involve using machine learning to improve hand detection performance in complex backgrounds.
Noise tolerant color image segmentation using support vector machineeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Gabor filter is a powerful way to enhance biometric images like fingerprint images in order to extract correct features from these images, Gabor filter used in extracting features directly asin iris images, and sometimes Gabor filter has been used for texture analysis. In fingerprint images The even symmetric Gabor filter is contextual filter or multi-resolution filter will be used to enhance fingerprint imageby filling small gaps (low-pass effect) in the direction of the ridge (black regions) and to increase the discrimination between ridge and valley (black and white regions) in the direction, orthogonal to the ridge, the proposed method in applying Gabor filter on fingerprint images depending on translated fingerprint image into binary image after applying some simple enhancing methods to partially overcome time consuming problem of the Gabor filter.
Tracking and counting human in visual surveillance systemiaemedu
This document summarizes a proposed system for tracking and counting humans in a visual surveillance system. The system first performs background subtraction on input video frames to detect foreground objects. It applies this process to both grayscale and binary image formats, and selects the better-performing format. Features are then extracted from detected objects. Objects are tracked frame-to-frame based on these features. Counting is performed by analyzing pixels representing detected humans across frames. Experimental results on videos with various challenges like shadows, illumination changes and occlusions show the system can accurately track and count humans, with near real-time performance.
Similar to An Automated Method for Segmentation of the Hand In Sign Language (20)
A Study on Translucent Concrete Product and Its Properties by Using Optical F...IJMER
- Translucent concrete is a concrete based material with light-transferring properties,
obtained due to embedded light optical elements like Optical fibers used in concrete. Light is conducted
through the concrete from one end to the other. This results into a certain light pattern on the other
surface, depending on the fiber structure. Optical fibers transmit light so effectively that there is
virtually no loss of light conducted through the fibers. This paper deals with the modeling of such
translucent or transparent concrete blocks and panel and their usage and also the advantages it brings
in the field. The main purpose is to use sunlight as a light source to reduce the power consumption of
illumination and to use the optical fiber to sense the stress of structures and also use this concrete as an
architectural purpose of the building
Developing Cost Effective Automation for Cotton Seed DelintingIJMER
A low cost automation system for removal of lint from cottonseed is to be designed and
developed. The setup consists of stainless steel drum with stirrer in which cottonseeds having lint is mixed
with concentrated sulphuric acid. So lint will get burn. This lint free cottonseed treated with lime water to
neutralize acidic nature. After water washing this cottonseeds are used for agriculter purpose
Study & Testing Of Bio-Composite Material Based On Munja FibreIJMER
The incorporation of natural fibres such as munja fiber composites has gained
increasing applications both in many areas of Engineering and Technology. The aim of this study is to
evaluate mechanical properties such as flexural and tensile properties of reinforced epoxy composites.
This is mainly due to their applicable benefits as they are light weight and offer low cost compared to
synthetic fibre composites. Munja fibres recently have been a substitute material in many weight-critical
applications in areas such as aerospace, automotive and other high demanding industrial sectors. In
this study, natural munja fibre composites and munja/fibreglass hybrid composites were fabricated by a
combination of hand lay-up and cold-press methods. A new variety in munja fibre is the present work
the main aim of the work is to extract the neat fibre and is characterized for its flexural characteristics.
The composites are fabricated by reinforcing untreated and treated fibre and are tested for their
mechanical, properties strictly as per ASTM procedures.
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)IJMER
Hybrid engine is a combination of Stirling engine, IC engine and Electric motor. All these 3 are
connected together to a single shaft. The power source of the Stirling engine will be a Solar Panel. The aim of
this is to run the automobile using a Hybrid engine
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...IJMER
This document summarizes research on the fabrication and characterization of bio-composite materials using sunnhemp fibre. The document discusses how sunnhemp fibre was used to reinforce an epoxy matrix through hand lay-up methods. Various mechanical properties of the bio-composites were tested, including tensile, flexural, and impact properties. The results of the mechanical tests on the bio-composite specimens are presented. Potential applications of the sunnhemp fibre bio-composites are also suggested, such as in fall ceilings, partitions, packaging, automotive interiors, and toys.
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...IJMER
The Greenstone belts of Karnataka are enriched in BIFs in Dharwar craton, where Iron
formations are confined to the basin shelf, clearly separated from the deeper-water iron formation that
accumulated at the basin margin and flanking the marine basin. Geochemical data procured in terms of
major, trace and REE are plotted in various diagrams to interpret the genesis of BIFs. Al2O3, Fe2O3 (T),
TiO2, CaO, and SiO2 abundances and ratios show a wide variation. Ni, Co, Zr, Sc, V, Rb, Sr, U, Th,
ΣREE, La, Ce and Eu anomalies and their binary relationships indicate that wherever the terrigenous
component has increased, the concentration of elements of felsic such as Zr and Hf has gone up. Elevated
concentrations of Ni, Co and Sc are contributed by chlorite and other components characteristic of basic
volcanic debris. The data suggest that these formations were generated by chemical and clastic
sedimentary processes on a shallow shelf. During transgression, chemical precipitation took place at the
sediment-water interface, whereas at the time of regression. Iron ore formed with sedimentary structures
and textures in Kammatturu area, in a setting where the water column was oxygenated.
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...IJMER
In this paper, the mechanical characteristics of C45 medium carbon steel are investigated
under various working conditions. The main characteristic to be studied on this paper is impact toughness
of the material with different configurations and the experiment were carried out on charpy impact testing
equipment. This study reveals the ability of the material to absorb energy up to failure for various
specimen configurations under different heat treated conditions and the corresponding results were
compared with the analysis outcome
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...IJMER
Robot guns are being increasingly employed in automotive manufacturing to replace
risky jobs and also to increase productivity. Using a single robot for a single operation proves to be
expensive. Hence for cost optimization, multiple guns are mounted on a single robot and multiple
operations are performed. Robot Gun structure is an efficient way in which multiple welds can be done
simultaneously. However mounting several weld guns on a single structure induces a variety of
dynamic loads, especially during movement of the robot arm as it maneuvers to reach the weld
locations. The primary idea employed in this paper, is to model those dynamic loads as equivalent G
force loads in FEA. This approach will be on the conservative side, and will be saving time and
subsequently cost efficient. The approach of the paper is towards creating a standard operating
procedure when it comes to analysis of such structures, with emphasis on deploying various technical
aspects of FEA such as Non Linear Geometry, Multipoint Constraint Contact Algorithm, Multizone
meshing .
Static Analysis of Go-Kart Chassis by Analytical and Solid Works SimulationIJMER
This paper aims to do modelling, simulation and performing the static analysis of a go
kart chassis consisting of Circular beams. Modelling, simulations and analysis are performed using 3-D
modelling software i.e. Solid Works and ANSYS according to the rulebook provided by Indian Society of
New Era Engineers (ISNEE) for National Go Kart Championship (NGKC-14).The maximum deflection is
determined by performing static analysis. Computed results are then compared to analytical calculation,
where it is found that the location of maximum deflection agrees well with theoretical approximation but
varies on magnitude aspect.
In récent year various vehicle introduced in market but due to limitation in
carbon émission and BS Séries limitd speed availability vehicle in the market and causing of
environnent pollution over few year There is need to decrease dependancy on fuel vehicle.
bicycle is to be modified for optional in the future To implement new technique using change in
pedal assembly and variable speed gearbox such as planetary gear optimise speed of vehicle
with variable speed ratio.To increase the efficiency of bicycle for confortable drive and to
reduce torque appli éd on bicycle. we introduced epicyclic gear box in which transmission done
throgh Chain Drive (i.e. Sprocket )to rear wheel with help of Epicyclical gear Box to give
number of différent Speed during driving.To reduce torque requirent in the cycle with change in
the pedal mechanism
Integration of Struts & Spring & Hibernate for Enterprise ApplicationsIJMER
This document discusses integrating the Spring, Struts, and Hibernate frameworks to develop enterprise applications. It provides an overview of each framework and their features. The Spring Framework is a lightweight, modular framework that allows for inversion of control and aspect-oriented programming. It can be used to develop any or all tiers of an application. The document proposes an architecture for an e-commerce website that integrates these three frameworks, with Spring handling the business layer, Struts the presentation layer, and Hibernate the data access layer. This modular approach allows for clear separation of concerns and reduces complexity in application development.
Microcontroller Based Automatic Sprinkler Irrigation SystemIJMER
Microcontroller based Automatic Sprinkler System is a new concept of using
intelligence power of embedded technology in the sprinkler irrigation work. Designed system replaces
the conventional manual work involved in sprinkler irrigation to automatic process. Using this system a
farmer is protected against adverse inhuman weather conditions, tedious work of changing over of
sprinkler water pipe lines & risk of accident due to high pressure in the water pipe line. Overall
sprinkler irrigation work is transformed in to a comfortableautomatic work. This system provides
flexibility & accuracy in respect of time set for the operation of a sprinkler water pipe lines. In present
work the author has designed and developed an automatic sprinkler irrigation system which is
controlled and monitored by a microcontroller interfaced with solenoid valves.
On some locally closed sets and spaces in Ideal Topological SpacesIJMER
This document introduces and studies the concept of δˆ s-locally closed sets in ideal topological spaces. Some key points:
- A subset A is δˆ s-locally closed if A can be written as the intersection of a δˆ s-open set and a δˆ s-closed set.
- Various properties of δˆ s-locally closed sets are introduced and characterized, including relationships to other concepts like generalized locally closed sets.
- It is shown that a subset A is δˆ s-locally closed if and only if A can be written as the intersection of a δˆ s-open set and the δˆ s-closure of A.
- Theore
Intrusion Detection and Forensics based on decision tree and Association rule...IJMER
This paper present an approach based on the combination of, two techniques using
decision tree and Association rule mining for Probe attack detection. This approach proves to be
better than the traditional approach of generating rules for fuzzy expert system by clustering methods.
Association rule mining for selecting the best attributes together and decision tree for identifying the
best parameters together to create the rules for fuzzy expert system. After that rules for fuzzy expert
system are generated using association rule mining and decision trees. Decision trees is generated for
dataset and to find the basic parameters for creating the membership functions of fuzzy inference
system. Membership functions are generated for the probe attack. Based on these rules we have
created the fuzzy inference system that is used as an input to neuro-fuzzy system. Fuzzy inference
system is loaded to neuro-fuzzy toolbox as an input and the final ANFIS structure is generated for
outcome of neuro-fuzzy approach. The experiments and evaluations of the proposed method were
done with NSL-KDD intrusion detection dataset. As the experimental results, the proposed approach
based on the combination of, two techniques using decision tree and Association rule mining
efficiently detected probe attacks. Experimental results shows better results for detecting intrusions as
compared to others existing methods
Natural Language Ambiguity and its Effect on Machine LearningIJMER
This document discusses natural language ambiguity and its effect on machine learning. It begins by introducing different types of ambiguity that exist in natural languages, including lexical, syntactic, semantic, discourse, and pragmatic ambiguities. It then examines how these ambiguities present challenges for computational linguistics and machine translation systems. Specifically, it notes that ambiguity is a major problem for computers in processing human language as they lack the world knowledge and context that humans use to resolve ambiguities. The document concludes by outlining the typical process of machine translation and how ambiguities can interfere with tasks like analysis, transfer, and generation of text in the target language.
Today in era of software industry there is no perfect software framework available for
analysis and software development. Currently there are enormous number of software development
process exists which can be implemented to stabilize the process of developing a software system. But no
perfect system is recognized till yet which can help software developers for opting of best software
development process. This paper present the framework of skillful system combined with Likert scale. With
the help of Likert scale we define a rule based model and delegate some mass score to every process and
develop one tool name as MuxSet which will help the software developers to select an appropriate
development process that may enhance the probability of system success.
Material Parameter and Effect of Thermal Load on Functionally Graded CylindersIJMER
The present study investigates the creep in a thick-walled composite cylinders made
up of aluminum/aluminum alloy matrix and reinforced with silicon carbide particles. The distribution
of SiCp is assumed to be either uniform or decreasing linearly from the inner to the outer radius of
the cylinder. The creep behavior of the cylinder has been described by threshold stress based creep
law with a stress exponent of 5. The composite cylinders are subjected to internal pressure which is
applied gradually and steady state condition of stress is assumed. The creep parameters required to
be used in creep law, are extracted by conducting regression analysis on the available experimental
results. The mathematical models have been developed to describe steady state creep in the composite
cylinder by using von-Mises criterion. Regression analysis is used to obtain the creep parameters
required in the study. The basic equilibrium equation of the cylinder and other constitutive equations
have been solved to obtain creep stresses in the cylinder. The effect of varying particle size, particle
content and temperature on the stresses in the composite cylinder has been analyzed. The study
revealed that the stress distributions in the cylinder do not vary significantly for various combinations
of particle size, particle content and operating temperature except for slight variation observed for
varying particle content. Functionally Graded Materials (FGMs) emerged and led to the development
of superior heat resistant materials.
An Implementation of I2C Slave Interface using Verilog HDLIJMER
This document describes the implementation of an I2C slave interface using Verilog HDL. It introduces the I2C protocol which uses only two bidirectional lines (SDA and SCL) for communication. The document discusses the I2C protocol specifications including start/stop conditions, addressing, read/write operations, and acknowledgements. It then provides details on designing an I2C slave module in Verilog that responds to commands from an I2C master and allows synchronization through clock stretching. The module is simulated in ModelSim and synthesized in Xilinx. Simulation waveforms demonstrate successful read and write operations to the slave device.
Discrete Model of Two Predators competing for One PreyIJMER
This paper investigates the dynamical behavior of a discrete model of one prey two
predator systems. The equilibrium points and their stability are analyzed. Time series plots are obtained
for different sets of parameter values. Also bifurcation diagrams are plotted to show dynamical behavior
of the system in selected range of growth parameter
Application of Parabolic Trough Collectorfor Reduction of Pressure Drop in Oi...IJMER
Pipelines are the least expensive and most effective method for the oil transportation.
Due to high viscosity of crude oil, the pressure drop and pumping power requirements are very high.
So it is necessary to bring down the viscosity of crude oil. Heated pipelines are used reduce the oil
viscosity by increasing the oil temperature. Electrical heating and direct flame heating are the common
method used for heating the oil pipeline. In this work, a new application of Parabolic Trough Collector
in the field of oil pipeline transport is introduced for reducing pressure drop in oil pipelines. Oil
pipeline is heated by applying concentrated solar radiation on the pipe surface using a Parabolic
Trough Collector in which the oil pipeline acts as the absorber pipe. 3-D steady state analysis is
carried out on a heated oil pipeline using commercial CFD software package ANSYS Fluent 14.5. In
this work an effort is made to investigate the effect of concentrated solar radiation for reducing
pressure drop in the oil pipeline. The results from the numerical analysis shows that the pressure drop
in oil pipeline is get reduced by heating the pipe line using concentrated solar radiation. From this
work, the application of PTC in oil pipeline transportation is justified.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...amsjournal
The Fourth Industrial Revolution is transforming industries, including healthcare, by integrating digital,
physical, and biological technologies. This study examines the integration of 4.0 technologies into
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An Automated Method for Segmentation of the Hand In Sign Language
1. International
OPEN ACCESS Journal
Of Modern Engineering Research (IJMER)
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 5| May. 2014 | 11 |
An Automated Method for Segmentation of the Hand In
Sign Language
B. Luna-Benoso1
, R. Flores-Carapia2
, O. Camacho-Nieto 3
, A. L. Barrales-
López4
, H. Flores-Gutiérrez5
1
(Escuela Superior de Cómputo, Instituto Politécnico Nacional, México)
2, 3, 4, 5
(Centro de Innovación y DesarrolloTecnológico en Cómputo, Instituto Politécnico Nacional, México)
I. Introducción
Around of 70 million deaf people in the world use the signs language as their maternal language or
main language [1]. The difficulties faced the people deaf-mute in the daily life are quite due to the difficult
understanding or total ignorance of signs language meaning that use. The signs language is a communication
mean for the people with deficiency hearing, where the words and sentences are represented for hand gestures,
and have grammatical structures perfectly defined. Due to the difficult communication that be between a deaf
people that use the signs language for take charge of the translation process with the finality of study to deeply
the deaf culture with psychotherapeutic purpose[2]. A system capable of carry out the automatic recognition of
sign language without the need of an individual translator can eventually provide an excellent tool for deaf
people to communicate with people that disown the language, and this way we can achieve a better way to live
[3]. This paper proposes a methodology for carry out the automatic segmentation of hand in images that show
the Mexican sign language (figure 1). For this, images were captured by a people webcam doing some Mexican
sign language, later with digital treatment techniques of images basing in the spatial domain was obtained the
sign segmentation doing by the individual.
Figure 1: Mexican sign language
II. Basic concepts
In the section three will be shown the proposed method, however for that, make use of the
mathematical morphology, and for that reason, in the following lines we show the concerning concepts for the
mathematical morphology.
The mathematical morphology is a framework based exclusively in the set theory. The original theory
developed by Georges Matheron and Jean Serra, has been used with huge success in the digital processing of
binary images. There are two fundamental operations in the mathematical morphology: dilatation and the
erosion. The dilatation is a term referred to increase, expand, rise, among other actions, of any object. On the
other hand, the erosion is referred to the contraction, reduction, decrease, among other actions, of any object. In
the following lines are the accuracy definitions of the fundamental operations of the mathematical morphology.
Abstract: This paper presents an automated method for hand segmentation in images that make use of
signs language. For this, used an images bank that was captured by a webcam to which were applied
spatial domain methods for hand segmentation.
Keywords: Digital images processing, spatial domain methods, images segmentation.
2. An Automated Method for Segmentation of the hand in Sign Language
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 5| May. 2014 | 12 |
2.1 Dilation
Started the short dilation operation study. For this, consider in all that follow, discrete sets 2-dimensional, that
is, subsets of ℤ2
.
Definition 2.1.1:BeA ⊆ ℤ2
. The set A is denoted byA −
, is defined by:
A−
= −x|x ∈ A (1)
Definition 2.1.2:BeA ⊆ ℤ2
andx ∈ ℤ2
. The translation of A by x denoted by (A)xis defined as:
(A)x = a + x|a ∈ A (2)
The following definition shows the formal concept of what is dilation operation.
Definition 2.1.3: BeA, B ⊆ ℤ2
, the dilation of A by B, denoted byA ⊕ B, is the sum of Minkowskiof A and B;
this is:
A ⊕ B = a + b|a ∈ A and b ∈ B (3)
The set B of the previous definition will be called structuring element.
Figure 2: Representing the set A, the structuring element B = 0,0 , 1,0 , (2,0) and the dilationA ⊕ B
Theorem 2.1.1:Be A, B ⊆ ℤ2
. It holds that:
A ⊕ B = x|(B−
)x ∩ A ≠ ∅ (4)
Demonstration:
x ∈ A ⊕ BIfx= a + b for somea ∈ A and b ∈ B if x − b = a for some a ∈ A and b ∈ B if x − b = a for some
a ∈ A and −b ∈ B−
if a − x = −b for some a ∈ A and −b ∈ B−
if a ∈ (B−
)x and a ∈ A if a ∈ (B−
)x ∩ A for
some a if Bx
−
∩ A ≠ ∅.
The previous theorem allows us to define an alternative form, which is the dilation of a set A by the structuring
element B.
2.2 Erosion
Then be show the formal concept of what is erosion.
Definition 2.2.1: Be A, B ⊆ ℤ2
. The erosion of A by B, denoted by A ⊖ B, the subtraction of Minkowski of Aby
B; this is:
A ⊖ B = x ∈ ℤ2
|x + b ∈ A for each b ∈ B (5)
Figure 3: Representación the set A, the structuring element B = −1, 0 , 0,0 , (1,0) and the erosion A ⊖ B
3. An Automated Method for Segmentation of the hand in Sign Language
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 5| May. 2014 | 13 |
Theorem 2.2.1: be A, B ⊆ ℤ2
, it holds that:
A ⊖ B = x|(B)x ⊆ A (6)
Demonstration:
x ∈ A ⊖ BIfx + b ∈ A for each b ∈ B by the definition 2.2.1 if (B)x ⊆ A by the definition 2.1.2
The previous theorem allows us to define an alternative form, which is the erosion of a setA by the structuring
element B.
III. Proposed method
Before to arrive on detail with proposed method, it’s necessary give the definition about a digital
image. A digital image is a Two-dimensional function f (x, y), of the light intensity (Sheen/brightness) on a
space point, so (x, y), the coordinates for that point [9]. Inasmuch as a digital image is a function f (x, y)
discretised on the space coordinates so in the sheen, sometimes could be representative like a two-dimensional
matrix Fij = (fij)mxn , where m and n are the size of the image and fij = f (xi, xj).
The proposed method is dived in two parts: 1) image acquisition and 2) signal segmentation of the individual
done.
1) Image acquisition: With webcam help, to get images of persons doing a signal of LSM set. Like in
figure 4.
Figure 4: Imageacquisition.
2) Signal segmentation: For this part it could be considerate the next stages:
Step 1. The image need to be separate in three components red, green and blue (RGB) and it was considerate the
red component because of the human skin is more sharp for this component (figure 5).
Step 2. It was considerate to grayscale from red component, this is, the value of the red component is copied to
the green and blue component, thereby obtaining the image in grayscale.
Figure 5: Decomposing an image into its three RGB components, and grayscale.
4. An Automated Method for Segmentation of the hand in Sign Language
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 5| May. 2014 | 14 |
Step 3. The histogram was obtained of the image with gray levels in the range [0, 255], where the histogram is a
discrete function H k represents the number of colors of each gray level (k = 0, …, 255) [9].
Step 4. Given an image f x, y and two variables u and v, the binarization by thresholding is used defined as
follows:
binij =
0
255
if u ≤ fij ≤ v
if fij < 𝑢 𝑜𝑟 fij > 𝑣
Shown in Figure 6, that the histogram shows two maximum peaks at 0 and 255, to eliminate these peaks, were
considered as thresholds u = 20 and v = 185.
Figure 6: Show the first 4 steps applied to a color image.
Once obtained, the binarized image, we proceeded to locate the corresponding part of the hand, for it is
considered that:
Step 5. Consider a mask size x within a mask size y as shown in Figure 7. Variablesu and v be two to locate the
area corresponding to the hand image, the following function is implemented for each point i, j on the image, it
is My
ij
mask size and centered at i, j , the function Tijis defined at each point i, j as:
Tij : My
ij
→ [0, 255]
Where
𝑇𝑖𝑗 𝑟, 𝑠 =
𝑓𝑟𝑠
255
𝑖𝑓 𝐴 𝑥 ≥ 𝑢 𝑎𝑛𝑑 𝐴 𝑦 − 𝐴 𝑥 ≤ 𝑣
𝑖𝑓 𝐴 𝑥 < 𝑢 𝑜𝑟 𝐴 𝑦 − 𝐴 𝑥 > 𝑣
With𝐴 𝑥 and 𝐴 𝑦 the areas enclosed by the masks of size 𝑥 and 𝑦 respectively.
Figure 7: Masks of size x and y.
Step 6.Once located the section of image binary corresponding of the hand, morphological erosion operator was
applied.
5. An Automated Method for Segmentation of the hand in Sign Language
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 5| May. 2014 | 15 |
Step 7. Morphological dilation operator was applied.
The figure 8 shows the process of applying erosion to the image hand segmented with a Moore neighborhood,
and subsequently applying dilation 6 times with the same vicinity. Finally, shows the image of the hand
segmented to color.
Figure 8: Process segmentation of the hand to locate the sign on.
IV. Conclusión
This paper is presented an automated method for segmentation of abnormalities in digital
mammography images. The method was applied an images bank that was captured by a webcam The proposed
segmentation method can be a useful to the development of computational systems that address the problem of
patterns classification focused on the problem of sign language.
Acknowledgements
The authors would like to thank the Instituto Politécnico Nacional (SecretaríaAcadémica, EDI,
COFAA, SIP, ESCOM and CIDETEC), the CONACyT and SNI for their economical support to develop this
work.
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