Image Processing, Analysis & and Machine Vision - A MATLAB Companion

by Svoboda, Tomas; Kybic, Jan; Hlavac, Vaclav

• ISBN13: 9780495295952
• ISBN10: 0495295957
• Edition: 1st
• Format: Paperback
• Copyright: 2007-08-31
• Publisher: Cengage Learning

Summary

This book is a companion book to the comprehensive text entitled Image Processing, Analysis, and Machine Vision by M. Sonka, V. Hlavac, and R. Boyle. This workbook provides additional material for readers of Sonka and is similarly structured. Written for students, teachers and practitioners to acquire practical understanding in a hands on fashion, this book provides the reader with short-answer questions, problems and selected algorithms from the main text using MATLAB in levels of varying difficulty. These resources can be used as extra practice for students to reinforce the material studied within the main text or can be useful as test materials for teachers. A solutions manual is available for Instructors for the problems within this workbook.

Table of Contents

Introduction to the companion book	p. ix
Structure of the companion book	p. ix
The WWW page for the companion book	p. x
Useful learning material by others	p. x
Introduction	p. 1
Problems	p. 1
Viewing an image: image_view_demo	p. 2
The image, its representations and properties	p. 7
Problems	p. 7
Displaying a coarse binary image: coarse_pixels_draw	p. 9
Distance transform: dist_trans_demo	p. 10
Border of a region: region_border_demo	p. 12
The image, its mathematical and physical background	p. 15
Problems	p. 15
Convolution, shift-multiply-add approach: conv_demo	p. 17
Discrete Fourier Transform: dft_edu	p. 19
Inverse DFT: idft_edu	p. 20
1D Discrete Fourier Transform: dft1d_demo	p. 21
2D Discrete Fourier Transform: dft2d_demo	p. 23
Basis functions for the 2D Discrete Cosine Transform: dct2base	p. 25
Principal Component Analysis: pca	p. 28
Data structures for image analysis	p. 33
Problems	p. 34
Matlab data structures: structures	p. 35
Displaying image values: showim_values	p. 35
Co-occurrence matrix: cooc	p. 36
Integral image construction: integralim	p. 39
Image pre-processing	p. 42
Problems	p. 43
Grayscale transformation, histogram equalization: hist_equal	p. 47
Geometric transformation: imgeomt	p. 49
Smoothing using a rotating mask: rotmask	p. 53
Image sharpening by Laplacian: imsharpen	p. 57
Harris corner detector: harris	p. 60
Frequency filtering: buttfilt	p. 62
Segmentation I	p. 66
Problems	p. 66
Iterative threshold selection: imthresh	p. 69
Line detection using Hough transform: hough_lines	p. 71
Dynamic programming boundary tracing: dpboundary	p. 73
Region merging via boundary melting: regmerge	p. 75
Removal of small regions: remsmall	p. 78
Segmentation II	p. 81
Problems	p. 81
Mean shift segmentation: meanshsegm	p. 83
Active contours (snakes): snake	p. 85
Gradient vector flow snakes: mgvf	p. 91
Level sets: levelset	p. 93
Graph cut segmentation: graphcut	p. 97
Shape representation and description	p. 102
Problems	p. 102
B-spline interpolation: bsplineinterp	p. 104
Convex hull construction: convexhull	p. 107
Region descriptors: regiondescr	p. 110
Boundary descriptors: boundarydescr	p. 115
Object recognition	p. 119
Problems	p. 119
Maximum probability classification for normal data: maxnormalclass	p. 122
Linear separability and basic classifiers: linsep_demo	p. 123
Recognition of hand-written numerals: ocr_demo	p. 126
Adaptive boosting: adaboost	p. 127
Image understanding	p. 134
Problems	p. 134
Random sample consensus: ransac	p. 136
Gaussian mixture model estimation: gaussianmixture	p. 139
Point distribution models: pointdistrmodel	p. 144
Active shape model fit: asmfit	p. 150
3D vision, geometry	p. 154
Problems	p. 154
Homography estimation from point correspondences-DLT method: u2Hdlt	p. 156
Mathematical description of the camera: cameragen	p. 159
Visualize a camera in a 3D plot: showcams	p. 161
Decomposition of the projection matrix P: P2KRtC	p. 162
Isotropic point normalization: pointnorm	p. 163
Fundamental matrix-8-point algorithm: u2Fd1t	p. 164
Geometrical Explanation of Epipolar Geometry: u2Fd1t_demo	p. 166
3D point reconstruction-linear method: uP2Xd1t	p. 168
Use of 3D vision	p. 171
Problems	p. 171
Iterative closest point matching: vtxicrp	p. 171
Mathematical morphology	p. 174
Problems	p. 175
Top hat transformation: tophat	p. 176
Object detection using opening: objdetect	p. 178
Sequential thinning: thinning	p. 180
Ultimate erosion: ulterosion	p. 183
Binary granulometry: granulometry	p. 185
Watershed segmentation: wshed	p. 188
Image data compression	p. 190
Problems	p. 190
Huffman code: huffman	p. 192
Predictive compression: dpcm	p. 197
JPEG compression pictorially, step by step: jpegcomp_demo	p. 203
Texture	p. 207
Problems	p. 207
Haralick texture descriptors: haralick	p. 209
Wavelet texture descriptors: waveletdescr	p. 213
Texture based segmentation: texturesegm	p. 215
L-system interpreter: lsystem	p. 219
Motion analysis	p. 224
Problems	p. 224
Adaptive background modeling by using a mixture of Gaussians: bckggm	p. 225
Particle filtering: particle_filtering	p. 232
Importance sampling: importance_sampling	p. 241
Kernel-based tracking: kernel_based_tracking	p. 242
Acknowledgments	p. 247
References	p. 248
Index	p. 252
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