计算机视觉特征提取与图像处理

内容概要

作者:(英)尼克松 等

书籍目录

ContentsPreface ......................................................................................................................xiAbout the authors ................................................................................................. xviiCHAPTER 1 Introduction ............................................................................. 11.1 Overview ......................................................................................11.2 Human and computer vision........................................................21.3 The human vision system ............................................................41.3.1 The eye.............................................................................51.3.2 The neural system............................................................81.3.3 Processing ........................................................................91.4 Computer vision systems...........................................................121.4.1 Cameras..........................................................................121.4.2 Computer interfaces.......................................................151.4.3 Processing an image ......................................................171.5 Mathematical systems................................................................191.5.1 Mathematical tools ........................................................191.5.2 Hello Matlab, hello images! ..........................................201.5.3 Hello Mathcad! ..............................................................251.6 Associated literature ..................................................................301.6.1 Journals, magazines, and conferences...........................301.6.2 Textbooks.......................................................................311.6.3 The Web.........................................................................341.7 Conclusions ................................................................................351.8 References ..................................................................................35CHAPTER 2 Images, Sampling, and FrequencyDomain Processing............................................................. 372.1 Overview ....................................................................................372.2 Image formation.........................................................................382.3 The Fourier transform................................................................422.4 The sampling criterion...............................................................492.5 The discrete Fourier transform ..................................................532.5.1 1D transform..................................................................532.5.2 2D transform..................................................................572.6 Other properties of the Fourier transform.................................632.6.1 Shift invariance..............................................................632.6.2 Rotation..........................................................................652.6.3 Frequency scaling ..........................................................662.6.4 Superposition (linearity) ................................................67v2.7 Transforms other than Fourier...................................................682.7.1 Discrete cosine transform..............................................682.7.2 Discrete Hartley transform ............................................702.7.3 Introductory wavelets ....................................................712.7.4 Other transforms ............................................................782.8 Applications using frequency domain properties......................782.9 Further reading...........................................................................802.10 References..................................................................................81CHAPTER 3 Basic Image Processing Operations............................. 833.1 Overview ....................................................................................833.2 Histograms .................................................................................843.3 Point operators ...........................................................................863.3.1 Basic point operations ...................................................863.3.2 Histogram normalization ...............................................893.3.3 Histogram equalization..................................................903.3.4 Thresholding ..................................................................933.4 Group operations........................................................................983.4.1 Template convolution ....................................................983.4.2 Averaging operator ......................................................1013.4.3 On different template size ...........................................1033.4.4 Gaussian averaging operator .......................................1043.4.5 More on averaging.......................................................1073.5 Other statistical operators ........................................................1093.5.1 Median filter ................................................................1093.5.2 Mode filter ...................................................................1123.5.3 Anisotropic diffusion ...................................................1143.5.4 Force field transform ...................................................1213.5.5 Comparison of statistical operators .............................1223.6 Mathematical morphology.......................................................1233.6.1 Morphological operators..............................................1243.6.2 Gray-level morphology................................................1273.6.3 Gray-level erosion and dilation ...................................1283.6.4 Minkowski operators ...................................................1303.7 Further reading.........................................................................1343.8 References ................................................................................134CHAPTER 4 Low-Level Feature Extraction (includingedge detection)..................................................................1374.1 Overview ..................................................................................1384.2 Edge detection..........................................................................1404.2.1 First-order edge-detection operators ...........................1404.2.2 Second-order edge-detection operators .......................161vi Contents4.2.3 Other edge-detection operators ...................................1704.2.4 Comparison of edge-detection operators ....................1714.2.5 Further reading on edge detection...............................1734.3 Phase congruency.....................................................................1734.4 Localized feature extraction ....................................................1804.4.1 Detecting image curvature (corner extraction) ...........1804.4.2 Modern approaches: region/patch analysis .................1934.5 Describing image motion.........................................................1994.5.1 Area-based approach ...................................................2004.5.2 Differential approach...................................................2044.5.3 Further reading on optical flow...................................2114.6 Further reading.........................................................................2124.7 References ................................................................................212CHAPTER 5 High-Level Feature Extraction: Fixed ShapeMatching ..............................................................................2175.1 Overview ..................................................................................2185.2 Thresholding and subtraction ..................................................2205.3 Template matching ..................................................................2225.3.1 Definition .....................................................................2225.3.2 Fourier transform implementation...............................2305.3.3 Discussion of template matching ................................2345.4 Feature extraction by low-level features .................................2355.4.1 Appearance-based approaches.....................................2355.4.2 Distribution-based descriptors .....................................2385.5 Hough transform ......................................................................2435.5.1 Overview......................................................................2435.5.2 Lines.............................................................................2435.5.3 HT for circles...............................................................2505.5.4 HT for ellipses .............................................................2555.5.5 Parameter space decomposition ..................................2585.5.6 Generalized HT............................................................2715.5.7 Other extensions to the HT .........................................2875.6 Further reading.........................................................................2885.7 References ................................................................................289CHAPTER 6 High-Level Feature Extraction: DeformableShape Analysis ...........................................................2936.1 Overview ..................................................................................2936.2 Deformable shape analysis ......................................................2946.2.1 Deformable templates..................................................2946.2.2 Parts-based shape analysis...........................................297Contents vii6.3 Active contours (snakes)..........................................................2996.3.1 Basics ...........................................................................2996.3.2 The Greedy algorithm for snakes................................3016.3.3 Complete (Kass) snake implementation......................3086.3.4 Other snake approaches...............................................3136.3.5 Further snake developments ........................................3146.3.6 Geometric active contours (level-set-basedapproaches) ..................................................................3186.4 Shape skeletonization ..............................................................3256.4.1 Distance transforms .....................................................3256.4.2 Symmetry.....................................................................3276.5 Flexible shape models—active shape and activeappearance................................................................................3346.6 Further reading.........................................................................3386.7 References ................................................................................338CHAPTER 7 Object Description.............................................................3437.1 Overview ..................................................................................3437.2 Boundary descriptions .............................................................3457.2.1 Boundary and region ...................................................3457.2.2 Chain codes..................................................................3467.2.3 Fourier descriptors .......................................................3497.3 Region descriptors ...................................................................3787.3.1 Basic region descriptors ..............................................3787.3.2 Moments ......................................................................3837.4 Further reading.........................................................................3957.5 References ................................................................................395CHAPTER 8 Introduction to Texture Description,Segmentation, and Classification ............................3998.1 Overview ..................................................................................3998.2 What is texture? .......................................................................4008.3 Texture description ..................................................................4038.3.1 Performance requirements ...........................................4038.3.2 Structural approaches ..................................................4038.3.3 Statistical approaches ..................................................4068.3.4 Combination approaches .............................................4098.3.5 Local binary patterns ...................................................4118.3.6 Other approaches .........................................................4178.4 Classification............................................................................4178.4.1 Distance measures .......................................................4178.4.2 The k-nearest neighbor rule.........................................4248.4.3 Other classification approaches...................................428viii Contents8.5 Segmentation............................................................................4298.6 Further reading.........................................................................4318.7 References ................................................................................432CHAPTER 9 Moving Object Detection and Description ..............4359.1 Overview ..................................................................................4359.2 Moving object detection ..........................................................4379.2.1 Basic approaches .........................................................4379.2.2 Modeling and adapting to the (static) background .....4429.2.3 Background segmentation by thresholding .................4479.2.4 Problems and advances................................................4509.3 Tracking moving features ........................................................4519.3.1 Tracking moving objects .............................................4519.3.2 Tracking by local search .............................................4529.3.3 Problems in tracking....................................................4559.3.4 Approaches to tracking................................................4559.3.5 Meanshift and Camshift ..............................................4579.3.6 Recent approaches .......................................................4729.4 Moving feature extraction and description .............................4749.4.1 Moving (biological) shape analysis.............................4749.4.2 Detecting moving shapes by shape matchingin image sequences ......................................................4769.4.3 Moving shape description............................................4809.5 Further reading.........................................................................4839.6 References ................................................................................484CHAPTER 10 Appendix 1: Camera Geometry Fundamentals........48910.1 Image geometry .......................................................................48910.2 Perspective camera ..................................................................49010.3 Perspective camera model .......................................................49110.3.1 Homogeneous coordinates and projectivegeometry.......................................................................49110.3.2 Perspective camera model analysis .............................49610.3.3 Parameters of the perspective camera model..............49910.4 Affine camera ..........................................................................50010.4.1 Affine camera model ...................................................50110.4.2 Affine camera model and the perspectiveprojection .....................................................................50310.4.3 Parameters of the affine camera model.......................50410.5 Weak perspective model..........................................................50510.6 Example of camera models .....................................................50710.7 Discussion ................................................................................51710.8 References................................................................................518Contents ixCHAPTER 11 Appendix 2: Least Squares Analysis .......................51911.1 The least squares criterion .......................................................51911.2 Curve fitting by least squares ..................................................521CHAPTER 12 Appendix 3: Principal Components Analysis .......52512.1 Principal components analysis ..............................................52512.2 Data ........................................................................................52612.3 Covariance .............................................................................52612.4 Covariance matrix..................................................................52912.5 Data transformation ...............................................................53012.6 Inverse transformation ...........................................................53112.7 Eigenproblem.........................................................................53212.8 Solving the eigenproblem......................................................53312.9 PCA method summary ..........................................................53312.10 Example .................................................................................53412.11 References..............................................................................540CHAPTER 13 Appendix 4: Color Images.......................................54113.1 Color images..........................................................................54213.2 Tristimulus theory..................................................................54213.3 Color models..........................................................................54413.3.1 The colorimetric equation .......................................54413.3.2 Luminosity function ................................................54513.3.3 Perception based color models: the CIE RGBand CIE XYZ...........................................................54713.3.4 Uniform color spaces: CIE LUV and CIE LAB.....56213.3.5 Additive and subtractive color models: RGBand CMY .................................................................56813.3.6 Luminance and chrominance color models:YUV, YIQ, and YCbCr...........................................57513.3.7 Perceptual color models: HSV and HLS ................58313.3.8 More color models...................................................59913.4 References..............................................................................600Index ......................................................................................................................601x Contents

编辑推荐

尼克松和阿瓜多编著的《计算机视觉特征提取与图像处理》是由英国南安普顿大学的Mark Nixon教授和Sportradar公司的Alberto S.Aguado在第二版的基础上，于2012年9月推出的最新改版之作（第3版）。本次改版，主要的变化是将高级特征提取，分为固定形状匹配与可变形形状分析两部分，并增加了新的一章内容：运动对象检测与描述。具体地，在简要介绍计算机视觉的基础概念和基本的图像处理运算后，重点讨论了低级和高级的特征提取，包括边缘检测、固定形状匹配和可变形形状分析。

作者简介

尼克松和阿瓜多编著的《计算机视觉特征提取与图像处理》是由英国南安普顿大学的MarkNixon教授和Sportradar公司的Alberto S.Aguado在第二版的基础上，于2012年9月推出的最新改版之作。本次改版，主要的变化是将高级特征提取，分为固定形状匹配与可变形形状分析两部分，并增加了新的一章内容：运动对象检测与描述。具体地，在简要介绍计算机视觉的基础概念和基本的图像处理运算后，重点讨论了低级和高级的特征提取，包括边缘检测、固定形状匹配和可变形形状分析。此外，对目标描述，纹理描述、分割及分类，以及运动对象检测等都进行深入的阐述。它突出了计算机视觉的主要问题——特征提取，以清晰、简洁的语言，阐述了图像处理和计算机视觉的基础理论与技术。

    《计算机视觉特征提取与图像处理》可作为高等学校电子工程、计算机科学、计算机工程等专业本科生的双语教材，也可以作为图像、视频信号处理，模式识别和计算机视觉研究方向的博士生、硕士研究生，以及相关专业的科研工作者的参考用书。

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