LEADER 05643nam 2200685Ia 450 001 9910790326903321 005 20200520144314.0 010 $a0-12-397824-6 035 $a(CKB)2670000000233488 035 $a(EBL)998617 035 $a(OCoLC)821862638 035 $a(SSID)ssj0000737390 035 $a(PQKBManifestationID)12341377 035 $a(PQKBTitleCode)TC0000737390 035 $a(PQKBWorkID)10787040 035 $a(PQKB)10273119 035 $a(Au-PeEL)EBL998617 035 $a(CaPaEBR)ebr10589757 035 $a(CaONFJC)MIL938594 035 $a(MiAaPQ)EBC998617 035 $a(EXLCZ)992670000000233488 100 $a20120907d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aFeature extraction & image processing for computer vision$b[electronic resource] /$fMark S. Nixon, Alberto S. Aguado 205 $a3rd ed. 210 $aOxford $cAcademic$d2012 215 $a1 online resource (628 p.) 300 $aPrevious edition published as: Feature extraction and image processing / Mark S. Nixon, Alberto S. Aguado, 2008. 311 $a0-12-396549-7 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Feature Extraction & Image Processing for Computer Vision; Copyright page; Contents; Preface; What is new in the third edition?; Why did we write this book?; The book and its support; In gratitude; Final message; About the authors; 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 Matlab, hello images!; 1.5.3 Hello Mathcad! 327 $a1.6 Associated literature1.6.1 Journals, magazines, and conferences; 1.6.2 Textbooks; 1.6.3 The Web; 1.7 Conclusions; 1.8 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 1D transform; 2.5.2 2D 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 327 $a2.7.3 Introductory wavelets2.7.3.1 Gabor wavelet; 2.7.3.2 Haar 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; 3.4.5 More on averaging; 3.5 Other statistical operators 327 $a3.5.1 Median filter3.5.2 Mode filter; 3.5.3 Anisotropic diffusion; 3.5.4 Force field transform; 3.5.5 Comparison of statistical operators; 3.6 Mathematical morphology; 3.6.1 Morphological operators; 3.6.2 Gray-level morphology; 3.6.3 Gray-level erosion and dilation; 3.6.4 Minkowski operators; 3.7 Further reading; 3.8 References; 4 Low-level feature extraction (including edge detection); 4.1 Overview; 4.2 Edge detection; 4.2.1 First-order edge-detection operators; 4.2.1.1 Basic operators; 4.2.1.2 Analysis of the basic operators; 4.2.1.3 Prewitt edge-detection operator 327 $a4.2.1.4 Sobel edge-detection operator4.2.1.5 The Canny edge detector; 4.2.2 Second-order edge-detection operators; 4.2.2.1 Motivation; 4.2.2.2 Basic operators: the Laplacian; 4.2.2.3 The Marr-Hildreth operator; 4.2.3 Other edge-detection operators; 4.2.4 Comparison of edge-detection operators; 4.2.5 Further reading on edge detection; 4.3 Phase congruency; 4.4 Localized feature extraction; 4.4.1 Detecting image curvature (corner extraction); 4.4.1.1 Definition of curvature; 4.4.1.2 Computing differences in edge direction; 4.4.1.3 Measuring curvature by changes in intensity (differentiation) 327 $a4.4.1.4 Moravec and Harris detectors 330 $aThis book is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, ""The main strength of the proposed book is the exemplar code of the algorithms."" Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral fi 606 $aComputer vision 606 $aComputer vision$xMathematics 606 $aPattern recognition systems 606 $aImage processing$xDigital techniques 615 0$aComputer vision. 615 0$aComputer vision$xMathematics. 615 0$aPattern recognition systems. 615 0$aImage processing$xDigital techniques. 676 $a006.37 700 $aNixon$b Mark S$01465063 701 $aAguado$b Alberto S$01465064 701 2$aNixon$b Mark S$01465063 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910790326903321 996 $aFeature extraction & image processing for computer vision$93674907 997 $aUNINA