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A Beginner's Guide to Image Shape Feature Extraction Techniques.

By: Contributor(s): Material type: TextTextSeries: Intelligent Signal Processing and Data Analysis SeriesPublisher: Milton : Taylor & Francis Group, 2019Copyright date: ©2020Edition: 1st edDescription: 1 online resource (147 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781000034301
Subject(s): Genre/Form: Additional physical formats: Print version:: A Beginner's Guide to Image Shape Feature Extraction TechniquesDDC classification:
  • 006.37
LOC classification:
  • TA1634 .C435 2020
Online resources:
Contents:
Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Authors -- 1: Introduction to Shape Feature -- 1.1 Introduction -- 1.1.1 4-Neighborhood -- 1.1.2 d-Neighborhood -- 1.1.3 8-Neighborhood -- 1.1.4 Connectivity -- 1.1.5 Connected Components -- 1.2 Importance of Shape Features -- 1.3 Properties of Efficient Shape Features -- 1.4 Types of Shape Features -- 1.4.1 Contour-Based Shape Representation and Description Techniques -- 1.4.1.1 Global Methods -- 1.4.1.2 Structural Methods -- 1.4.1.3 Limitations of the Structural Approach -- 1.4.2 Region-Based Shape Representation and Description Techniques -- 1.5 Summary -- References -- 2: One-Dimensional Function Shape Features -- 2.1 Complex Coordinate (ComC) -- 2.2 Centroid Distance Function (CDF) -- 2.3 Tangent Angle (TA) -- 2.4 Contour Curvature (CC) -- 2.5 Area Function (AF) -- 2.6 Triangle Area Representation (TAR) -- 2.7 Chord Length Function (CLF) -- 2.8 Summary -- References -- 3: Geometric Shape Features -- 3.1 Center of Gravity (CoG) -- 3.2 Axis of Minimum Inertia (AMI) -- 3.3 Average Bending Energy (ABE) -- 3.4 Eccentricity -- 3.4.1 Principal Axes Method -- 3.4.2 Minimum Bounding Rectangle (MBR) -- 3.5 Circularity Ratio (CR) -- 3.6 Ellipticity -- 3.6.1 Ellipse Variance (EV) -- 3.6.2 Ellipticity Based on Moment Invariants -- 3.7 Rectangularity -- 3.7.1 Smallest Bounding Rectangle (SBR) -- 3.7.2 Rectangular Discrepancy Method (RDM) -- 3.7.3 Robust Smallest Bounding Rectangle (RSBR) -- 3.8 Convexity -- 3.9 Solidity -- 3.10 Euler Number (EN) -- 3.11 Profiles -- 3.12 Hole Area Ratio (HAR) -- 3.13 Summary -- References -- 4: Polygonal Approximation Shape Features -- 4.1 Merging Method (MM) -- 4.1.1 Distance Threshold Method (DTM) -- 4.1.2 Tunnelling Method (TM) -- 4.1.3 Polygon Evolution by Vertex Deletion (PEVD) -- 4.2 Splitting Method (SM).
4.3 Minimum Perimeter Polygon (MPP) -- 4.3.1 Data Preparation for MPP -- 4.3.2 MPP Algorithm -- 4.4 Dominant Point (DP) Detection -- 4.5 K-means Method -- 4.6 Genetic Algorithm (GA) -- 4.6.1 Encoding -- 4.6.2 Fitness -- 4.6.3 Genetic Operators or Control Parameters -- 4.7 Ant Colony Optimization (ACO) Method -- 4.7.1 Initialization -- 4.7.2 Node Transition Rule -- 4.7.3 Pheromone Updating Rule -- 4.7.4 Stopping Criterion -- 4.8 Tabu Search (TS) -- 4.8.1 Initialization -- 4.8.2 Definition of Moves -- 4.8.3 Aspiration Criteria (AC) -- 4.9 Summary -- References -- 5: Spatial Interrelation Shape Features -- 5.1 Adaptive Grid Resolution (AGR) -- 5.2 Bounding Box (BB) -- 5.3 Convex Hull (CH) -- 5.4 Chain Code (CC) -- 5.4.1 Basic -- 5.4.2 Differential -- 5.4.3 Re-sampling -- 5.4.4 Vertex -- 5.4.5 Chain Code Histogram (CCH) -- 5.5 Smooth Curve Decomposition (SCD) -- 5.6 Beam Angle Statistics (BAS) -- 5.7 Shape Matrix (SM) -- 5.7.1 Square Model -- 5.7.2 Polar Model -- 5.8 Shape Context (SC) -- 5.9 Chord Distribution (CD) -- 5.10 Shock Graphs (SG) -- 5.11 Summary -- References -- 6: Moment Shape Feature -- 6.1 Contour Moment (CM) -- 6.2 Geometric Invariant Moment (GIM) -- 6.3 Zernike Moment (ZM) -- 6.4 Radial Chebyshev Moment (RCM) -- 6.5 Legendre Moment (LM) -- 6.6 Homocentric Polar-Radius Moment (HPRM) -- 6.7 Orthogonal Fourier-Mellin Moment (OFMM) -- 6.8 Pseudo-Zernike Moment (PZM) -- 6.9 Summary -- References -- 7: Scale-Space Shape Features -- 7.1 Curvature Scale Space (CSS) -- 7.1.1 Extreme Curvature Scale Space (ECSS) -- 7.1.2 Direct Curvature Scale Space (DCSS) -- 7.1.3 Affine Resilient Curvature Scale Space (ARCSS) -- 7.2 Morphological Scale Space (MSS) -- 7.3 Intersection Points Map (IPM) -- 7.4 Summary -- References -- 8: Shape Transform Domain Shape Feature -- 8.1 Fourier Descriptors -- 8.1.1 One-Dimensional Fourier Descriptors.
8.1.2 Region-Based Fourier Descriptor -- 8.2 Wavelet Transform -- 8.3 Angular Radial Transformation (ART) -- 8.4 Shape Signature Harmonic Embedding -- 8.5 R-Transform -- 8.6 Shapelet Descriptor (SD) -- 8.7 Summary -- References -- 9: Applications of Shape Features -- 9.1 Digit Recognition -- 9.2 Character Recognition -- 9.3 Fruit Recognition -- 9.4 Leaf Recognition -- 9.5 Hand Gesture Recognition -- 9.6 Summary -- References -- Index.
Summary: This book emphasizes various image shape feature extraction methods which are necessary for image shape recognition and classification. Focussing on a shape feature extraction technique used in content-based image retrieval (CBIR), it explains different applications of image shape features in the field of content-based image retrieval.
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Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Authors -- 1: Introduction to Shape Feature -- 1.1 Introduction -- 1.1.1 4-Neighborhood -- 1.1.2 d-Neighborhood -- 1.1.3 8-Neighborhood -- 1.1.4 Connectivity -- 1.1.5 Connected Components -- 1.2 Importance of Shape Features -- 1.3 Properties of Efficient Shape Features -- 1.4 Types of Shape Features -- 1.4.1 Contour-Based Shape Representation and Description Techniques -- 1.4.1.1 Global Methods -- 1.4.1.2 Structural Methods -- 1.4.1.3 Limitations of the Structural Approach -- 1.4.2 Region-Based Shape Representation and Description Techniques -- 1.5 Summary -- References -- 2: One-Dimensional Function Shape Features -- 2.1 Complex Coordinate (ComC) -- 2.2 Centroid Distance Function (CDF) -- 2.3 Tangent Angle (TA) -- 2.4 Contour Curvature (CC) -- 2.5 Area Function (AF) -- 2.6 Triangle Area Representation (TAR) -- 2.7 Chord Length Function (CLF) -- 2.8 Summary -- References -- 3: Geometric Shape Features -- 3.1 Center of Gravity (CoG) -- 3.2 Axis of Minimum Inertia (AMI) -- 3.3 Average Bending Energy (ABE) -- 3.4 Eccentricity -- 3.4.1 Principal Axes Method -- 3.4.2 Minimum Bounding Rectangle (MBR) -- 3.5 Circularity Ratio (CR) -- 3.6 Ellipticity -- 3.6.1 Ellipse Variance (EV) -- 3.6.2 Ellipticity Based on Moment Invariants -- 3.7 Rectangularity -- 3.7.1 Smallest Bounding Rectangle (SBR) -- 3.7.2 Rectangular Discrepancy Method (RDM) -- 3.7.3 Robust Smallest Bounding Rectangle (RSBR) -- 3.8 Convexity -- 3.9 Solidity -- 3.10 Euler Number (EN) -- 3.11 Profiles -- 3.12 Hole Area Ratio (HAR) -- 3.13 Summary -- References -- 4: Polygonal Approximation Shape Features -- 4.1 Merging Method (MM) -- 4.1.1 Distance Threshold Method (DTM) -- 4.1.2 Tunnelling Method (TM) -- 4.1.3 Polygon Evolution by Vertex Deletion (PEVD) -- 4.2 Splitting Method (SM).

4.3 Minimum Perimeter Polygon (MPP) -- 4.3.1 Data Preparation for MPP -- 4.3.2 MPP Algorithm -- 4.4 Dominant Point (DP) Detection -- 4.5 K-means Method -- 4.6 Genetic Algorithm (GA) -- 4.6.1 Encoding -- 4.6.2 Fitness -- 4.6.3 Genetic Operators or Control Parameters -- 4.7 Ant Colony Optimization (ACO) Method -- 4.7.1 Initialization -- 4.7.2 Node Transition Rule -- 4.7.3 Pheromone Updating Rule -- 4.7.4 Stopping Criterion -- 4.8 Tabu Search (TS) -- 4.8.1 Initialization -- 4.8.2 Definition of Moves -- 4.8.3 Aspiration Criteria (AC) -- 4.9 Summary -- References -- 5: Spatial Interrelation Shape Features -- 5.1 Adaptive Grid Resolution (AGR) -- 5.2 Bounding Box (BB) -- 5.3 Convex Hull (CH) -- 5.4 Chain Code (CC) -- 5.4.1 Basic -- 5.4.2 Differential -- 5.4.3 Re-sampling -- 5.4.4 Vertex -- 5.4.5 Chain Code Histogram (CCH) -- 5.5 Smooth Curve Decomposition (SCD) -- 5.6 Beam Angle Statistics (BAS) -- 5.7 Shape Matrix (SM) -- 5.7.1 Square Model -- 5.7.2 Polar Model -- 5.8 Shape Context (SC) -- 5.9 Chord Distribution (CD) -- 5.10 Shock Graphs (SG) -- 5.11 Summary -- References -- 6: Moment Shape Feature -- 6.1 Contour Moment (CM) -- 6.2 Geometric Invariant Moment (GIM) -- 6.3 Zernike Moment (ZM) -- 6.4 Radial Chebyshev Moment (RCM) -- 6.5 Legendre Moment (LM) -- 6.6 Homocentric Polar-Radius Moment (HPRM) -- 6.7 Orthogonal Fourier-Mellin Moment (OFMM) -- 6.8 Pseudo-Zernike Moment (PZM) -- 6.9 Summary -- References -- 7: Scale-Space Shape Features -- 7.1 Curvature Scale Space (CSS) -- 7.1.1 Extreme Curvature Scale Space (ECSS) -- 7.1.2 Direct Curvature Scale Space (DCSS) -- 7.1.3 Affine Resilient Curvature Scale Space (ARCSS) -- 7.2 Morphological Scale Space (MSS) -- 7.3 Intersection Points Map (IPM) -- 7.4 Summary -- References -- 8: Shape Transform Domain Shape Feature -- 8.1 Fourier Descriptors -- 8.1.1 One-Dimensional Fourier Descriptors.

8.1.2 Region-Based Fourier Descriptor -- 8.2 Wavelet Transform -- 8.3 Angular Radial Transformation (ART) -- 8.4 Shape Signature Harmonic Embedding -- 8.5 R-Transform -- 8.6 Shapelet Descriptor (SD) -- 8.7 Summary -- References -- 9: Applications of Shape Features -- 9.1 Digit Recognition -- 9.2 Character Recognition -- 9.3 Fruit Recognition -- 9.4 Leaf Recognition -- 9.5 Hand Gesture Recognition -- 9.6 Summary -- References -- Index.

This book emphasizes various image shape feature extraction methods which are necessary for image shape recognition and classification. Focussing on a shape feature extraction technique used in content-based image retrieval (CBIR), it explains different applications of image shape features in the field of content-based image retrieval.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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