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Handbook of pattern recognition and computer vision / edited by C.H. Chen, P.S.P. Wang.

Contributor(s): Chen, C. H. (Chi-hau), 1937- | Wang, Patrick S-P. (Patrick Shen-pei)Material type: TextTextPublication details: River Edge, NJ : World Scientific, ©2005. Edition: 3rd edDescription: 1 online resource (ix, 639 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9789812775320; 9812775323Subject(s): Pattern recognition systems | Computer vision | Reconnaissance des formes (Informatique) | Vision par ordinateur | COMPUTERS -- Optical Data Processing | Computer vision | Pattern recognition systems | Patroonherkenning | Computers | Visuele waarneming | Inteligência artificial | Reconhecimento de padrõesGenre/Form: Electronic books. | Electronic books. Additional physical formats: Print version:: Handbook of pattern recognition and computer vision.DDC classification: 006.4 LOC classification: TK7882.P3 | H35 2005ebOther classification: 54.74 Online resources: Click here to access online
Contents:
Preface to the Third Edition; Part 1. Basic Methods in Pattern Recognition; Chapter 1.1 Statistical Pattern Recognition; Chapter 1.2 Hidden Markov Models for Spatio-Temporal Pattern Recognition; Chapter 1.3 A New Kernel-Based Formalization of Minimum Error Pattern Recognition; Chapter 1.4 Parallel Contextual Array Grammars with Trajectories; Chapter 1.5 Pattern Recognition with Local Invariant Features; Part 2. Basic Methods in Computer Vision; Chapter 2.1 Case-Based Reasoning for Image Analysis and Interpretation; Chapter 2.2 Multiple Image Geometry -- A Projective Viewpoint.
Chapter 2.3 Skeletonization in 3D Discrete Binary ImagesChapter 2.4 Digital Distance Transforms in 2D 3D and 4D; Chapter 2.5 Computing Global Shape Measures; Chapter 2.6 Texture Analysis with Local Binary Patterns; Part 3. Recognition Applications; Chapter 3.1 Document Analysis and Understanding; Chapter 3.2 Chinese Character Recognition; Chapter 3.3 Extraction of Words from Handwritten Legal Amounts on Bank Cheques; Chapter 3.4 OCR Assessment of Printed-Fonts for Enhancing Human Vision; Chapter 3.5 Clustering and Classification of Web Documents Using a Graph Model.
Chapter 3.6 Automated Detection of Masses in MammogramsChapter 3.7 Wavelet-Based Kalman Filtering in Scale Space for Image Fusion; Chapter 3.8 Multisensor Fusion with Hyperspectral Imaging Data: Detection and Classification; Chapter 3.9 Independent Component Analysis of Functional Magnetic Resonance Imaging Data; Part 4. Human Identification; Chapter 4.1 Multimodal Emotion Recognition; Chapter 4.2 Gait-Based Human Identification from a Monocular Video Sequence; Chapter 4.3 Palmprint Authentication System; Chapter 4.4 Reconstruction of High-Resolution Facial Images for Visual Surveillance.
Chapter 4.5 Object Recognition with Deformable Feature Graphs: Faces Hands and Cluttered ScenesChapter 4.6 Hierarchical Classification and Feature Reduction for Fast Face Detection; Part 5. System and Technology; Chapter 5.1 Tracking and Classifying Moving Objects Using Single or Multiple Cameras; Chapter 5.2 Performance Evaluation of lmage Segmentation Algorithms; Chapter 5.3 Contents-Based Video Analysis for Knowledge Discovery; Chapter 5.4 Object-Process Methodology and Its Applications to Image Processing and Pattern Recognition.
Chapter 5.5 Musical Style Recognition -- A Quantitative ApproachChapter 5.6 Auto-Detector: Mobile Automatic Number Plate Recognition; Chapter 5.7 Omnidirectional Vision; Index.
Summary: The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures. Recognition applications include character recognition and document analysis, detection of digital mammograms, remote sensing image fusion, and analysis of functional magnetic resonance imaging data, etc. There are six chapters on current ac.
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Revised edition of: Handbook of pattern recognition & computer vision.

Print version record.

Includes bibliographical references.

Preface to the Third Edition; Part 1. Basic Methods in Pattern Recognition; Chapter 1.1 Statistical Pattern Recognition; Chapter 1.2 Hidden Markov Models for Spatio-Temporal Pattern Recognition; Chapter 1.3 A New Kernel-Based Formalization of Minimum Error Pattern Recognition; Chapter 1.4 Parallel Contextual Array Grammars with Trajectories; Chapter 1.5 Pattern Recognition with Local Invariant Features; Part 2. Basic Methods in Computer Vision; Chapter 2.1 Case-Based Reasoning for Image Analysis and Interpretation; Chapter 2.2 Multiple Image Geometry -- A Projective Viewpoint.

Chapter 2.3 Skeletonization in 3D Discrete Binary ImagesChapter 2.4 Digital Distance Transforms in 2D 3D and 4D; Chapter 2.5 Computing Global Shape Measures; Chapter 2.6 Texture Analysis with Local Binary Patterns; Part 3. Recognition Applications; Chapter 3.1 Document Analysis and Understanding; Chapter 3.2 Chinese Character Recognition; Chapter 3.3 Extraction of Words from Handwritten Legal Amounts on Bank Cheques; Chapter 3.4 OCR Assessment of Printed-Fonts for Enhancing Human Vision; Chapter 3.5 Clustering and Classification of Web Documents Using a Graph Model.

Chapter 3.6 Automated Detection of Masses in MammogramsChapter 3.7 Wavelet-Based Kalman Filtering in Scale Space for Image Fusion; Chapter 3.8 Multisensor Fusion with Hyperspectral Imaging Data: Detection and Classification; Chapter 3.9 Independent Component Analysis of Functional Magnetic Resonance Imaging Data; Part 4. Human Identification; Chapter 4.1 Multimodal Emotion Recognition; Chapter 4.2 Gait-Based Human Identification from a Monocular Video Sequence; Chapter 4.3 Palmprint Authentication System; Chapter 4.4 Reconstruction of High-Resolution Facial Images for Visual Surveillance.

Chapter 4.5 Object Recognition with Deformable Feature Graphs: Faces Hands and Cluttered ScenesChapter 4.6 Hierarchical Classification and Feature Reduction for Fast Face Detection; Part 5. System and Technology; Chapter 5.1 Tracking and Classifying Moving Objects Using Single or Multiple Cameras; Chapter 5.2 Performance Evaluation of lmage Segmentation Algorithms; Chapter 5.3 Contents-Based Video Analysis for Knowledge Discovery; Chapter 5.4 Object-Process Methodology and Its Applications to Image Processing and Pattern Recognition.

Chapter 5.5 Musical Style Recognition -- A Quantitative ApproachChapter 5.6 Auto-Detector: Mobile Automatic Number Plate Recognition; Chapter 5.7 Omnidirectional Vision; Index.

The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures. Recognition applications include character recognition and document analysis, detection of digital mammograms, remote sensing image fusion, and analysis of functional magnetic resonance imaging data, etc. There are six chapters on current ac.

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