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Computer Science - Image Processing | Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization

Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization

Mokhtarian, F., Bober, M.

2003, XIX, 431 p.

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MPEG-7 is the first international standard which contains a number of key techniques from Computer Vision and Image Processing. The Curvature Scale Space technique was selected as a contour shape descriptor for MPEG-7 after substantial and comprehensive testing, which demonstrated the superior performance of the CSS-based descriptor.

Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization is based on key publications on the CSS technique, as well as its multiple applications and generalizations. The goal was to ensure that the reader will have access to the most fundamental results concerning the CSS method in one volume. These results have been categorized into a number of chapters to reflect their focus as well as content. The book also includes a chapter on the development of the CSS technique within MPEG standardization, including details of the MPEG-7 testing and evaluation processes which led to the selection of the CSS shape descriptor for the standard.

The book can be used as a supplementary textbook by any university or institution offering courses in computer and information science.

Content Level » Research

Keywords » Active contour - Canny edge detector - Computer Vision - Information - MPEG - MPEG-7 - Performance - affine transform - algorithms - classification - cognition - data compression - filtering - image processing - object recognition

Related subjects » Database Management & Information Retrieval - Image Processing - Information Systems and Applications - Mathematics - Security and Cryptology

Table of contents 

Preface. * 1: Multi-Scale Representations for Free-Form Planar Curves. 1.1. Introduction. 1.2. The Curvature Scale Space Image. 1.3. The Renormalized Curvature Scale Space Image. 1.4. The Resampled Curvature Scale Space Image. 1.5. Evolution and Arc Length Evolution Properties of Planar Curves. 1.6. Experiments, Discussion and Evaluation. 1.7. Concluding Remarks. * 2: Robust Free-Form Object Recognition through Curvature Scale Space. 2.1. Introduction. 2.2. Silhouette-Based Isolated Object Recognition. 2.3. Silhouette-Based Occluded Object Recognition. 2.4. Concluding Remarks. * 3: Image Database Retrieval Based on Shape Content. 3.1. Introduction. 3.2. The CSS Matching Algorithm. 3.3. Global Parameters. 3.4. Performance Evaluation. 3.5. Results for Original Method. 3.6. Comparison to Other methods. 3.7. The Problem of Shallow Concavities. 3.8. Performance Evaluation and Experimental Results. 3.9. Application to Chrysanthemum Leaf Classification. 3.10. Conclusions. * 4: CSS Under Affine Transforms / Non-Rigid Deformations. 4.1. Introduction. 4.2. CSS Image under Affine Transforms. 4.3. Affine Transforms and Affine Databases. 4.4. Affine Length. 4.5. Affine Curvature. 4.6. Implementation Issues. 4.7. Experiments and Results. 4.8. Comparison to Other Methods. 4.9. Concluding Remarks. * 5: Free-Form 3-D Object Retrieval from Arbitrary Viewpoints. 5.1. Introduction. 5.2. Multi-View 3-D Object Representation and Retrieval. 5.3. Robust Automatic Selection of Optimal Views. 5.4. Free-Form 3-D Object Retrieval with Occlusion from Arbitrary Viewpoints. 5.5. Conclusions. * 6: MPEG-7 Standardisation of the CSS Shape Descriptor. 6.1. Introduction. 6.2. MPEG-7 Overview. 6.3. MPEG-7 Shape Descriptors. 6.4. Contour-Based Shape Descriptor. 6.5. Region-Based Shape Descriptor. 6.6. MPEG-7 Performance Testing Methodology and Test Sets. 6.7. Experimental Performance Analysis and MPEG-7 Selection Process. 6.8. Example Applications of the CSS Shape Descriptor. 6.9. Conclusions. * 7: Robust Image Corner Detection through Curvature Scale Space. 7.1. Introduction. 7.2. literature Survey. 7.3. Canny Edge Detector. 7.4. Original CSS Corner Detection Method. 7.5. Original CSS Experimental Results and Discussion. 7.6. Enhanced CSS Corner Detection Method. 7.7. New CSS Experimental Results and Discussion. 7.8. Performance Evaluation of Corner Detection Algorithms under Similarity and Affine Transforms. 7.9. Conclusions. * 8: Fast Active Contour Convergence through CSS Filtering. 8.1. Introduction. 8.2. Literature Survey. 8.3. Smoothed Active Contour (SAC). 8.4. Experimental Results. 8.5. Conclusions. * 9: Multi-Scale Contour Data Compression and Reconstruction Using CSS. 9.1. Introduction. 9.2. Spline Fitting Techniques. 9.3. Contour Data Reconstruction throug

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