計算機視覺特徵提取與圖像處理（第三版）（英文版）

內容簡介

本書是由英國南安普頓大學的Mark Nixon教授和Sportradar公司的Alberto S. Aguado在第二版的基礎上，於2012年9月推出的最新改版之作（第3版）。本次改版，主要的變化是將高紙祖詢愚級特徵提取，分為固定形狀匹配與可變形形狀分析兩甩旬茅芝燥部分，並增加了新的一章內容：運動對象檢測與描述。熱獄愚具體地踏地雅，在簡要介紹計算機視覺的基礎概念和基本的圖像處理運算後，重點討論了低級和高級的特徵提取，包括邊緣檢戶朽葛記測、固定形狀多贈料匹配和可變形形狀分析。

圖書目錄

Contents

Preface ......................................................................................................................xi

About the authors ................................................................................................. xvii

CHAPTER 1 Introduction ............................................................................. 1

1.1 Overview ......................................................................................1

1.2 Human and computer vision........................................................2

1.3 The human vision system ............................................................4

1.3.1 The eye.............................................................................5

1.3.2 The neural system............................................................8

1.3.3 Processing ........................................................................9

1.4 Computer vision systems...........................................................12

1.4.1 Cameras..........................................................................12

1.4.2 Computer interfaces.......................................................15

1.4.3 Processing an image ......................................................17

1.5 Mathematical systems................................................................19

1.5.1 Mathematical tools ........................................................19

1.5.2 Hello Matlab, hello images! ..........................................20

1.5.3 Hello Mathcad! ..............................................................25

1.6 Associated literature ..................................................................30

1.6.1 Journals, magazines, and conferences...........................30

1.6.2 Textbooks.......................................................................31

1.6.3 The Web.........................................................................34

1.7 Conclusions ................................................................................35

1.8 References ..................................................................................35

CHAPTER 2 Images, Sampling, and Frequency

Domain Processing............................................................. 37

2.1 Overview ....................................................................................37

2.2 Image formation.........................................................................38

2.3 The Fourier transform................................................................42

2.4 The sampling criterion...............................................................49

2.5 The discrete Fourier transform ..................................................53

2.5.1 1D transform..................................................................53

2.5.2 2D transform..................................................................57

2.6 Other properties of the Fourier transform.................................63

2.6.1 Shift invariance..............................................................63

2.6.2 Rotation..........................................................................65

2.6.3 Frequency scaling ..........................................................66

2.6.4 Superposition (linearity) ................................................67

v

2.7 Transforms other than Fourier...................................................68

2.7.1 Discrete cosine transform..............................................68

2.7.2 Discrete Hartley transform ............................................70

2.7.3 Introductory wavelets ....................................................71

2.7.4 Other transforms ............................................................78

2.8 Applications using frequency domain properties......................78

2.9 Further reading...........................................................................80

2.10 References..................................................................................81

CHAPTER 3 Basic Image Processing Operations............................. 83

3.1 Overview ....................................................................................83

3.2 Histograms .................................................................................84

3.3 Point operators ...........................................................................86

3.3.1 Basic point operations ...................................................86

3.3.2 Histogram normalization ...............................................89

3.3.3 Histogram equalization..................................................90

3.3.4 Thresholding ..................................................................93

3.4 Group operations........................................................................98

3.4.1 Template convolution ....................................................98

3.4.2 Averaging operator ......................................................101

3.4.3 On different template size ...........................................103

3.4.4 Gaussian averaging operator .......................................104

3.4.5 More on averaging.......................................................107

3.5 Other statistical operators ........................................................109

3.5.1 Median filter ................................................................109

3.5.2 Mode filter ...................................................................112

3.5.3 Anisotropic diffusion ...................................................114

3.5.4 Force field transform ...................................................121

3.5.5 Comparison of statistical operators .............................122

3.6 Mathematical morphology.......................................................123

3.6.1 Morphological operators..............................................124

3.6.2 Gray-level morphology................................................127

3.6.3 Gray-level erosion and dilation ...................................128

3.6.4 Minkowski operators ...................................................130

3.7 Further reading.........................................................................134

3.8 References ................................................................................134

CHAPTER 4 Low-Level Feature Extraction (including

edge detection)..................................................................137

4.1 Overview ..................................................................................138

4.2 Edge detection..........................................................................140

4.2.1 First-order edge-detection operators ...........................140

4.2.2 Second-order edge-detection operators .......................161

vi Contents

4.2.3 Other edge-detection operators ...................................170

4.2.4 Comparison of edge-detection operators ....................171

4.2.5 Further reading on edge detection...............................173

4.3 Phase congruency.....................................................................173

4.4 Localized feature extraction ....................................................180

4.4.1 Detecting image curvature (corner extraction) ...........180

4.4.2 Modern approaches: region/patch analysis .................193

4.5 Describing image motion.........................................................199

4.5.1 Area-based approach ...................................................200

4.5.2 Differential approach...................................................204

4.5.3 Further reading on optical flow...................................211

4.6 Further reading.........................................................................212

4.7 References ................................................................................212

CHAPTER 5 High-Level Feature Extraction: Fixed Shape

Matching ..............................................................................217

5.1 Overview ..................................................................................218

5.2 Thresholding and subtraction ..................................................220

5.3 Template matching ..................................................................222

5.3.1 Definition .....................................................................222

5.3.2 Fourier transform implementation...............................230

5.3.3 Discussion of template matching ................................234

5.4 Feature extraction by low-level features .................................235

5.4.1 Appearance-based approaches.....................................235

5.4.2 Distribution-based descriptors .....................................238

5.5 Hough transform ......................................................................243

5.5.1 Overview......................................................................243

5.5.2 Lines.............................................................................243

5.5.3 HT for circles...............................................................250

5.5.4 HT for ellipses .............................................................255

5.5.5 Parameter space decomposition ..................................258

5.5.6 Generalized HT............................................................271

5.5.7 Other extensions to the HT .........................................287

5.6 Further reading.........................................................................288

5.7 References ................................................................................289

CHAPTER 6 High-Level Feature Extraction: Deformable

Shape Analysis ...........................................................293

6.1 Overview ..................................................................................293

6.2 Deformable shape analysis ......................................................294

6.2.1 Deformable templates..................................................294

6.2.2 Parts-based shape analysis...........................................297

Contents vii

6.3 Active contours (snakes)..........................................................299

6.3.1 Basics ...........................................................................299

6.3.2 The Greedy algorithm for snakes................................301

6.3.3 Complete (Kass) snake implementation......................308

6.3.4 Other snake approaches...............................................313

6.3.5 Further snake developments ........................................314

6.3.6 Geometric active contours (level-set-based

approaches) ..................................................................318

6.4 Shape skeletonization ..............................................................325

6.4.1 Distance transforms .....................................................325

6.4.2 Symmetry.....................................................................327

6.5 Flexible shape models—active shape and active

appearance................................................................................334

6.6 Further reading.........................................................................338

6.7 References ................................................................................338

CHAPTER 7 Object Description.............................................................343

7.1 Overview ..................................................................................343

7.2 Boundary descriptions .............................................................345

7.2.1 Boundary and region ...................................................345

7.2.2 Chain codes..................................................................346

7.2.3 Fourier descriptors .......................................................349

7.3 Region descriptors ...................................................................378

7.3.1 Basic region descriptors ..............................................378

7.3.2 Moments ......................................................................383

7.4 Further reading.........................................................................395

7.5 References ................................................................................395

CHAPTER 8 Introduction to Texture Description,

Segmentation, and Classification ............................399

8.1 Overview ..................................................................................399

8.2 What is texture? .......................................................................400

8.3 Texture description ..................................................................403

8.3.1 Performance requirements ...........................................403

8.3.2 Structural approaches ..................................................403

8.3.3 Statistical approaches ..................................................406

8.3.4 Combination approaches .............................................409

8.3.5 Local binary patterns ...................................................411

8.3.6 Other approaches .........................................................417

8.4 Classification............................................................................417

8.4.1 Distance measures .......................................................417

8.4.2 The k-nearest neighbor rule.........................................424

8.4.3 Other classification approaches...................................428

viii Contents

8.5 Segmentation............................................................................429

8.6 Further reading.........................................................................431

8.7 References ................................................................................432

CHAPTER 9 Moving Object Detection and Description ..............435

9.1 Overview ..................................................................................435

9.2 Moving object detection ..........................................................437

9.2.1 Basic approaches .........................................................437

9.2.2 Modeling and adapting to the (static) background .....442

9.2.3 Background segmentation by thresholding .................447

9.2.4 Problems and advances................................................450

9.3 Tracking moving features ........................................................451

9.3.1 Tracking moving objects .............................................451

9.3.2 Tracking by local search .............................................452

9.3.3 Problems in tracking....................................................455

9.3.4 Approaches to tracking................................................455

9.3.5 Meanshift and Camshift ..............................................457

9.3.6 Recent approaches .......................................................472

9.4 Moving feature extraction and description .............................474

9.4.1 Moving (biological) shape analysis.............................474

9.4.2 Detecting moving shapes by shape matching

in image sequences ......................................................476

9.4.3 Moving shape description............................................480

9.5 Further reading.........................................................................483

9.6 References ................................................................................484

CHAPTER 10 Appendix 1: Camera Geometry Fundamentals........489

10.1 Image geometry .......................................................................489

10.2 Perspective camera ..................................................................490

10.3 Perspective camera model .......................................................491

10.3.1 Homogeneous coordinates and projective

geometry.......................................................................491

10.3.2 Perspective camera model analysis .............................496

10.3.3 Parameters of the perspective camera model..............499

10.4 Affine camera ..........................................................................500

10.4.1 Affine camera model ...................................................501

10.4.2 Affine camera model and the perspective

projection .....................................................................503

10.4.3 Parameters of the affine camera model.......................504

10.5 Weak perspective model..........................................................505

10.6 Example of camera models .....................................................507

10.7 Discussion ................................................................................517

10.8 References................................................................................518

Contents ix

CHAPTER 11 Appendix 2: Least Squares Analysis .......................519

11.1 The least squares criterion .......................................................519

11.2 Curve fitting by least squares ..................................................521

CHAPTER 12 Appendix 3: Principal Components Analysis .......525

12.1 Principal components analysis ..............................................525

12.2 Data ........................................................................................526

12.3 Covariance .............................................................................526

12.4 Covariance matrix..................................................................529

12.5 Data transformation ...............................................................530

12.6 Inverse transformation ...........................................................531

12.7 Eigenproblem.........................................................................532

12.8 Solving the eigenproblem......................................................533

12.9 PCA method summary ..........................................................533

12.10 Example .................................................................................534

12.11 References..............................................................................540

CHAPTER 13 Appendix 4: Color Images.......................................541

13.1 Color images..........................................................................542

13.2 Tristimulus theory..................................................................542

13.3 Color models..........................................................................544

13.3.1 The colorimetric equation .......................................544

13.3.2 Luminosity function ................................................545

13.3.3 Perception based color models: the CIE RGB

and CIE XYZ...........................................................547

13.3.4 Uniform color spaces: CIE LUV and CIE LAB.....562

13.3.5 Additive and subtractive color models: RGB

and CMY .................................................................568

13.3.6 Luminance and chrominance color models:

YUV, YIQ, and YCbCr...........................................575

13.3.7 Perceptual color models: HSV and HLS ................583

13.3.8 More color models...................................................599

13.4 References..............................................................................600

Index ......................................................................................................................601

x Contents

計算機視覺特徵提取與圖像處理（第三版）（英文版）

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