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Feature Extraction and Image Processing

door Mark Nixon, Alberto Aguado

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Focusing on feature extraction while also covering issues and techniques such as image acquisition, sampling theory, point operations and low-level feature extraction, the authors have a clear and coherent approach that will appeal to a wide range of students and professionals.*Ideal module text for courses in artificial intelligence, image processing and computer vision*Essential reading for engineers and academics working in this cutting-edge field*Supported by free software on a companion website… (meer)
Onlangs toegevoegd doorzhuazhua88, Markober, Adam.Hunston, Mathworks
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Indeholder "Preface", "1. Introduction", " 1.1 Overview", " 1.2 Human and computer vision", " 1.3 The human vision system", " 1.3.1 The eye", " 1.3.2 The neural system", " 1.3.3 Processing", " 1.4 Computer vision systems", " 1.4.1 Cameras", " 1.4.2 Computer interfaces", " 1.4.3 Processing an image", " 1.5 Mathematical systems", " 1.5.1 Mathematical tools", " 1.5.2 Hello Mathcad, hello images!", " 1.5.3 Hello Matlab!", " 1.6 Associated literature", " 1.6.1 Journals and magazines", " 1.6.2 Textbooks", " 1.6.3 The web", " 1.7 References", "2. Images, sampling and frequency domain processing", " 2.1 Overview", " 2.2 Image formation", " 2.3 The Fourier transform", " 2.4 The sampling criterion", " 2.5 The discrete Fourier transform", " 2.5.1 One-dimensional transform", " 2.5.2 Two-dimensional transform", " 2.6 Other properties of the Fourier transform", " 2.6.1 Shift invariance", " 2.6.2 Rotation", " 2.6.3 Frequency scaling", " 2.6.4 Superposition (linearity)", " 2.7 Transforms other than Fourier", " 2.7.1 Discrete cosine transform", " 2.7.2 Discrete Hartley transform", " 2.7.3 Introductory wavelets: the Gabor wavelet", " 2.7.4 Other transforms", " 2.8 Applications using frequency domain properties", " 2.9 Further reading", " 2.10 References", "3. Basic image processing operations", " 3.1 Overview", " 3.2 Histograms", " 3.3 Point operators", " 3.3.1 Basic point operations", " 3.3.2 Histogram normalization", " 3.3.3 Histogram equalization", " 3.3.4 Thresholding", " 3.4 Group operations", " 3.4.1 Template convolution", " 3.4.2 Averaging operator", " 3.4.3 On different template size", " 3.4.4 Gaussian averaging operator", " 3.5 Other statistical operators", " 3.5.1 More on averaging", " 3.5.2 Median filter", " 3.5.3 Mode filter", " 3.5.4 Comparison of statistical operators", " 3.6 Further reading", " 3.7 References", "4. Low-level feature extraction (including edge detection)", " 4.1 Overview", " 4.2 First order edge detection operators", " 4.2.1 Basic operators", " 4.2.2 Analysis of the basic operators", " 4.2.3 Prewitt edge detection operator", " 4.2.4 Sobel edge detection operator", " 4.2.5 The Canny edge detection operator", " 4.3 Second order edge detection operators", " 4.3.1 Motivation", " 4.3.2 Basic operators: the Laplacian", " 4.3.3 The Marr-Hildreth operator", " 4.4 Other edge detection operators", " 4.4.1 Spacek operator", " 4.4.2 Petrou operator", " 4.5 Comparison of edge detection operators", " 4.6 Detecting image curvature", " 4.6.1 Computing differences in edge direction", " 4.6.2 Approximation to a continuous curve", " 4.6.3 Measuring curvature by changes in intensity", " 4.6.4 Autocorrelation as a measure of curvature", " 4.7 Describing image motion", " 4.7.1 Area-based approach", " 4-7-2 Differential approach", " 4.8 Further reading", " 4.9 References", "5. Feature extraction by shape matching", " 5.1 Overview", " 5.2 Thresholding and subtraction", " 5.3 Template matching", " 5.3.1 Definition", " 5.3.2 Fourier transform implementation", " 5.3.3 Discussion of template matching", " 5.4 Hough transform (HT)", " 5.4.1 Overview", " 5.4.2 Lines", " 5.4.3 HT for circles", " 5.4.4 HT for ellipses", " 5.4.5 Parameter space decomposition", " 5.5 Generalized Hough transform (GHT)", " 5.5.1 Formal definition of the GHT", " 5.5.2 Polar definition", " 5.5.3 The GHT technique", " 5.5.4 Invariant GHT", " 5.6 Other extensions to the Hough transform", " 5.7 Further reading", " 5.8 References", "6. Flexible shape extraction (snakes and other techniques)", " 6.1 Overview", " 6.2 Deformable templates", " 6.3 Active contours (snakes)", " 6.3.1 Basics", " 6.3.2 The greedy algorithm for snakes", " 6.3.3 Complete (Kass) snake implementation", " 6.3.4 Other snake approaches", " 6.3.5 Further snake developments", " 6.4 Discrete symmetry operator", " 6.5 Flexible shape models", " 6.6 Further reading", " 6.7 References", "7. Object description", " 7.1 Overview", " 7.2 Boundary descriptions", " 7.2.1 Boundary and region", " 7.2.2 Chain codes", " 7.2.3 Fourier descriptors", " 7.3 Region descriptors", " 7.3.1 Basic region descriptors", " 7.3.2 Moments", " 7.4 Further reading", " 7.5 References", "8. Introduction to texture description, segmentation and classification", " 8.1 Overview", " 8.2 What is texture?", " 8.3 Texture description", " 8.3.1 Performance requirements", " 8.3.2 Structural approaches", " 8.3.3 Statistical approaches", " 8.3.4 Combination approaches", " 8.4 Classification", " 8.4.1 The k-nearest neighbour rule", " 8.4.2 Other classification approaches", " 8.5 Segmentation", " 8.6 Further reading", " 8.7 References", "9. Appendices", " 9.1 Appendix 1: Example worksheets", " 9.1.1 References", " 9.2 Appendix 2: Least squares analysis", " 9.2.1 The least squares criterion", " 9.2.2 Curve fitting by least squares", " 9.3 Appendix 3: Example Mathcad worksheet for Chapter 3", " 9.4 Appendix 4: Abbreviated Matlab worksheet", "Index".

Glimrende bog med flere eksempler. Der er dog kommet nyere udgaver af bogen, men denne her er ok. Desværre er noget af satsen blevet skrevet om lige inden trykning og derfor er der opstået fejl, så check lige med en nyere udgave, hvis der er noget, der driller urimeligt. ( )
  bnielsen | Dec 29, 2015 |
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Focusing on feature extraction while also covering issues and techniques such as image acquisition, sampling theory, point operations and low-level feature extraction, the authors have a clear and coherent approach that will appeal to a wide range of students and professionals.*Ideal module text for courses in artificial intelligence, image processing and computer vision*Essential reading for engineers and academics working in this cutting-edge field*Supported by free software on a companion website

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