A Beginner's Guide to Image Shape Feature Extraction Techniques

ISBN-13: 9780367254391 / Angielski / Twarda / 2019 / 152 str.

Jyotismita Chaki; Nilanjan Dey

Opis

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.

Spis treści

Chapter 1: Introduction to Shape Feature

1.1 Introduction to Shape Feature

1.2 Importance of Shape Features

1.3 Properties of Efficient Shape Features

1.4 Types of Shape features

1.5 Summary

Chapter 2: One Dimensional Function Shape Features

2.1 Complex Coordinate

2.2 Centroid Distance Function

2.3 Tangent Angle

2.4 Contour Curvature

2.5 Area Function

2.6 Triangle Area Representation

2.7 Cord Length Function

2.8 Summary

Chapter 3: Geometric Shape Features

3.1 Center of Gravity

3.2 Axis of Minimum Inertia

3.3 Average Bending Energy

3.4 Eccentricity

3.5 Circularity ratio

3.6 Ellipticity

3.7 Rectangularity

3.8 Convexity

3.9 Solidity

3.10 Euler Number

3.11 Profiles

3.12 Hole Area Ratio

3.13 Summary

Chapter 4: Polygonal Approximation Shape Features

4.1 Merging Method

4.2 Splitting Method

4.3 Minimum Perimeter Polygon

4.4 Dominant Point Detection

4.5 K-means Method

4.6 Genetic Algorithm

4.7 Ant Colony Optimization Method

4.8 Tabu Search Method

4.9 Summary

Chapter 5: Spatial Interrelation Shape Features

5.1 Adaptive Grid Resolution

5.2 Bounding Box

5.3 Convex-Hull

5.4 Chain Code

5.5 Smooth Curve Decomposition

5.6 Beam Angle Statistics

5.7 Shape Matrix

5.8 Shape Context

5.9 Chord Distribution

5.10 Shock Graphs

5.11 Summary

　

Chapter 6: Moments Shape Feature

6.1 Contour Moment

6.2 Geometric Invariant Moment

6.3 Zernike Moment

6.4 Radial Chebyshev Moment

6.5 Legendre Moment

6.6 Homocentric Polar-Radius Moment

6.7 Orthogonal Fourier-Mellin Moment

6.8 Pseudo-Zernike Moment

6.9 Summary

Chapter 7: Scale Space Shape Features

7.1 Curvature Scale Space

7.2 Morphological Scale Space

7.3 Intersection Points Map

7.4 Summary

Chapter 8: Shape Transform Domain Shape Features

8.1 Fourier Descriptors

8.2 Wavelet Transforms

8.3 Angular Radial Transformation

8.4 Shape Signature Harmonic Embedding

8.5 -Transform

8.6 Shapelets Descriptor

8.7 Summary

Chapter 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