Contents目录
- Chapter 0: Introduction to the companion book本辅导书简介
- Chapter 1: Introduction 简介
- Viewing an image: image_view_demo 查看一张图像：image_view_demo
- Chapter 2: The image, its representations and properties
- Displaying a coarse binary image: coarse_pixels_draw
- Distance transform, an example: dist_trans_demo
- Border of a region, an example: region_border_demo
- Chapter 3: The image, its mathematical and physical background
- Convolution, shift-multiply-add approach: conv_demo
- Discrete Fourier Transform: dft_edu
- Inverse DFT: idft_edu
- 1D Discrete Fourier Transform: dft1d_demo
- 2D Discrete Fourier Transform: dft2d_demo
- Basis functions for the 2D Discrete Cosine Transform: dct2base
- Principal Component Analysis: pca
- Chapter 4: Data structures for image analysis
- MATLAB/ data structures: structures
- Displaying image values: showim_values
- Co-occurrence matrix: cooc 灰度共生矩阵
- Integral image construction: integralim
- Chapter 5: Image pre-processing
- Grayscale transformation, histogram equalization: hist_equal
- Geometric transformation: imgeomt
- Smoothing using a rotating mask: rotmask
- Image sharpening by Laplacian: imsharpen
- Harris corner detector: harris
- Frequency filtering: buttfilt
- Chapter 6: Segmentation I
- Iterative threshold selection: imthresh
- Line detection using Hough transform: hough_lines
- Dynamic programming boundary tracing: dpboundary
- Region merging via boundary melting: regmerge
- Removal of small regions: remsmall
- Chapter 7: Segmentation II
- Mean shift segmentation: meanshsegm
- Active contours (snakes): snake
- Gradient vector flow snakes: mgvf
- Level sets: levelset
- Graph cut segmentation: GraphCut
- Chapter 8: Shape representation and description
- B-spline interpolation: bsplineinterp
- Convex hull construction: convexhull
- Region descriptors: regiondescr
- Boundary descriptors: boundarydescr
- Chapter 9: Object recognition
- Maximum probability classification for normal data: maxnormalclass
- Linear separability and basic classifiers: linsep_demo
- Recognition of hand-written numerals: ocr_demo
- Adaptive boosting: adaboost
- Chapter 10: Image understanding
- Random sample consensus: ransac
- Gaussian mixture model estimation: gaussianmixture
- Point distribution models: pointdistrmodel
- Active shape model fit: asmfit
- Chapter 11: 3D vision, geometry
- Homography estimation from point correspondences---DLT method: u2Hdlt
- Mathematical description of the camera: cameragen
- Visualize a camera in a 3D plot: showcams
- Decomposition of the projection matrix P: P2KRtC
- Isotropic point normalization: pointnorm
- Fundamental matrix---8-point algorithm: u2Fdlt
- 3D point reconstruction---linear method: uP2Xdlt
- Chapter 12: Use of 3D vision
- Iterative closest point matching: vtxicrp
- Chapter 13: Mathematical morphology
- Top hat transformation: tophat
- Object detection using opening: objdetect
- Sequential thinning: thinning
- Ultimate erosion: ulterosion
- Binary granulometry: granulometry
- Watershed segmentation: wshed
- Chapter 14: Image data compression
- Huffman code: huffman
- Predictive compression: dpcm
- JPEG compression pictorially, step by step: jpegcomp_demo
- Chapter 15: Texture
- Haralick texture descriptors: haralick
- Wavelet texture descriptors: waveletdescr
- Texture based segmentation: texturesegm
- L-system interpreter: lsystem
- Chapter 16: Motion analysis
- Adaptive background modeling by using a mixture of Gaussians: bckggm
- Particle filtering: particle_filtering
- Importance sampling: importance_sampling
- Kernel-based tracking: kernel_based_tracking
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Last modified at 15:56, 28 April 2014 CEST.
关于机器视觉与机器学习的大量资源及书籍 可在线阅读：http://blog.exbot.net/archives/48
demo videos：http://visionbook.felk.cvut.cz/demos.html