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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