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Learning open 3 Computer vision in C++ with the opencv librar Adrian Kaehler and Gary bradski Beijing.Boston. Farnham Sebastopol. Tokyo OREILLY Learning opencv3 y Adrian Kaehler and Gary Bradski Copyright O 2017 Adrian Kaehler, Gary Bradski. All rights reserved Printed in the united states of america Published by O'Reilly Media, InC, 1005 Gravenstein Highway North, Sebastopol, CA 95472 OReilly books may be purchased for educational, business, or sales promotional use Online editions are alsoavailableformosttitles( rate/ Editor: Dawn schanafelt Indexer: ellen troutman Production editor: Kristen brown Interior Designer: David Futato Copyeditor: Rachel Monaghan Cover Designer: Karen Montgomery Proofreader: James Fraleigh Illustrator rebecca demarest December 2016: first edition Revision history for the first Edition 2016-12-09: First Release See The Oreilly logo is a registered trademark of O'Reilly Media, InC. Learning OpenCV 3, the cover image, and related trade dress are trademarks of o reilly media, inc While the publisher and the authors have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the authors disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights 978-1-491937990 Table of contents Preface 1. Overview What Is OpenCv? Who Uses OpenCv? 2 What Is Computer Vision? The Origin of OpenCⅤ OpenCV Block Diagram Speeding Up OpenCV with IPP Who Owns OpenCv? 10 Downloading and Installing OpenCV Installation 10 Getting the Latest Open Cv via Git 13 More Opencv documentation Supplied Documentation 14 Online documentation and the wiki 14 OpenCV Contribution Repository 17 Downloading and Building Contributed Modules 17 Portability 18 Summary Exercises 19 2. Introduction to OpenCV 21 Include files 21 Resources First Program-Display a picture 23 Second Program-Video 25 Moving around 27 A Simple transformation 31 A Not-So-Simple transformation 32 Input from a Camera 35 Writing to an avi file 36 Summary 38 Exercises 38 3. Getting to know opencv data types The basics 41 OpenCV Data Types 41 Overview of the Basic Types 42 Basic Types: Getting Down to Details 44 Helper Objects 52 Utility Functions The Template Structures 67 Summary 68 Exercises 69 4. Images and Large Array Types. ..............................................71 Dynamic and variable storage 71 The cv: Mat Class: N-Dimensional Dense Arrays Creating an Array Accessing Array Elements Individually 78 The N-ary Array Iterator: NAry MatIterator 81 Accessing Array Elements by Block 84 Matrix Expressions: Algebra and cv: Mat 85 Saturation Casting 87 More Things an array can do 88 The cv: SparseMat Class: Sparse Array 89 Accessing Sparse Array Elements 90 Functions Unique to Sparse arrays 92 Template Structures for Large Array Types 94 ummary 7 Exercises 97 5. Array Operations........... 99 More Things You Can Do with Arrays 99 cv: :abso 102 cv: :absdiffo 103 cv:addo 103 cv: :addWeightedo 104 cv: bitwise ando 106 iv Table of Contents cv: bitwise_noto 107 cv:: bitwise or( 107 cv: bitwise_xorO 108 cv: calcCovarMatrixO 108 tToPolaro cv: checkRangeo) cv: compareD 111 cv.: completesymm( cv: convertScaleAbso 112 cv: countNon Zero 113 cv: cvarrToMatO 113 dct 114 dft 115 cv:: determinant cV∷ divide 120 cv.:eigen( 120 Cv∴eXl pO 121 cv::extractImageCOIO 121 cv: fliPO 122 Cv.gemm 122 cv:getConvertElem( and cv: getConvertScaleElemo 123 cv: : idct 124 cv: idfto 124 CV.Inrange 124 cv: insertlmageCoIO 125 cv:invert( 126 cv: logo 126 CV: LUTO 127 cv:magnitude) 127 cv: Mahalanobis 128 Cv:maX 129 cv∴mean 130 cv: mean StdDevO 130 cv∴ merge 131 Cv∴mln 131 cv: min MaxIdxo 132 cv: minMaxLoco 133 cv: mix Channelso 134 cv: mulSpectrumsO 136 cv: multiply 136 cv: mulTransposedo 136 Table of contents cv:norm 137 cv: normalized 139 cv: Perspective Transform 140 haseo 141 cv: polar ToCarto cv: PowO 142 cv: anduo 143 cV∷ randn 143 cv: randShuffleO cv: reduce 144 cv: repeat) 145 cv: ScaleAddo 146 cv: setIdentityO 146 Cv: : solve( 147 ibicO 148 cv: SolvePolyo 149 149 cv:: SortIdxo 149 cv: : Split 150 150 cv:: Subtract 152 152 cv: trace 152 cv:transform 153 cv: transpose 153 Summary 154 Exercises 154 6. Drawing and Annotating Drawing Th nIngs 157 Line art and Filled polygons 158 Fonts and text 165 ummary 167 E 167 7. Functors in Opencv 169 Objects That“ Do Stuff 169 Principal Component Analysis(cv: PCA) 169 Singular Value Decomposition (CV: SVD) 173 Random Number generator(cv: RNG) 176 Summary Exercises 180 Table of contents 8. Image video and data files 183 HighGUl: Portable Graphics Toolkit 183 Working with Image files 185 Loading and Saving Images 185 a Note about codecs 188 Compression and decompression 188 Working with Video 189 Reading video with the cv Video Capture Object 190 Writing video with the cv: Video Writer Object 196 Data persistence 198 Writing to a cv: File Storage 198 Reading from a cv: FileStorage 200 cv. File Node 201 ummary 204 Exercises 204 9, Cross-Platform and native windows ,207 Working with Windows 207 HighGUI Native Graphical User Interface 208 Working with the Qt Backend 220 Integrating OpenCV with Full GUI Toolkits 232 Summary 247 Exercises 247 10. Filters and convolution 249 erview 249 Before We begin 249 Filters, Kernels, and Convolution 249 Border extrapolation and boundary conditions 251 Threshold Operations 255 Otsu's algorithm 258 Adaptive Threshold 259 Smoothing 261 Simple blur and the box filter 262 Median filter 265 Gaussian filter 266 Bilateral filter 267 Derivatives and gradients 269 The Sobel derivative 269 Scharr filter 272 The Laplacian 273 Image Morphology 275 Table of contents|ⅶi Dilation and erosion 276 The General Morphology Function 281 Opening and Closing 281 Morphological gradient 285 Top Hat and Black Hat 287 Making Your Own Kernel 289 Convolution with an Arbitrary Linear Filter 290 Applying a al Filter with cv: filter2DO 291 Applying a General Separable Filter with cv sep Filter2D 292 Kernel build 292 Summary 294 Exercises 294 11. General Image transformS......................... 299 Overview 299 Stretch, Shrink, Warp, and rotate 299 Uniform Resize 300 Image pyramids 302 ununiform mappings 306 Affine transformation 308 Perspective Transformation 313 General Remappings 316 Polar Mappings 317 Logpolar 318 Arbitrary mappings 322 Repair 323 Inpainting 324 Denoising 325 Histogram Equalization 328 u cv equalizeHist(: Contrast equalization 331 ummary 331 Exercises 332 12. Image Analysis.......... 鲁鲁非 335 Overview 335 Discrete fourier transform 336 cv: dft(: The Discrete Fourier Transform 336 cv: idfto: The Inverse Discrete Fourier Transform 339 cv: mulSpectrums: Spectrum Multiplication 339 Convolution Using Discrete Fourier Transforms 340 cv:: dct The Discrete Cosine Transform 342 cv: idct(: The Inverse Discrete Cosine Transform 343 viii Table of Contents

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