Practical Algorithms for Image Analysis with CD-ROM
In classic "cookbook style,” this book offers guided access for researchers and practitioners to techniques for the digital manipulation and analysis of images, ranging from the simplest steps to advanced functions. Drawing on their long experience as users and developers of image analysis algorithms and software, the authors present a description and implementation of the most suitable procedures in easy-to-use form. Each self-contained section treats a single operation, describing typical...
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This new edition's CD-ROM now has both the source code, and a graphic interface to make it easier to use.
1 Introduction 11.1 Introduction 11.2 Annotated Section Overview 51.3 A Guided Tour 142 Global Image Analysis 232.1 Intensity Histogram: Global Features 252.2 Histogram Transformations: Global Enhancement 292.3 Combining Images 392.4 Geometric Image Transformations 452.5 Color Image Transformations 533 Gray-Scale Image Analysis 583.1 Local Image Operations: Convolution 613.2 Noise Reduction 703.3 Edge Enhancement and Flat Fielding 773.4 Edge and Peak Point Detection 823.5 Advanced Edge Detection 923.6 Subsampling 993.7 Multiresolution Analysis 1033.8 Template Matching 1083.9 Gabor Wavelet Analysis 1123.10 Binarization 1184 Binary Image Analysis 1284.1 Morphological and Cellular Processing 1314.2 Binary Noise Removal 1394.3 Region Detection 1424.4 Shape Analysis: Geometrical Features and Moments 1544.5 Advanced Shape Analysis: Fourier Descriptors 1624.6 Convex Hull of Polygons 1664.7 Thinning 1704.8 Linewidth Determination 1744.9 Global Features and Image Profiles 1774.10 Hough Transform 1825 Analysis of Lines and Line Patterns 1865.1 Chain Coding 1885.2 Line Features and Noise Reduction 1945.3 Polygonalization 2015.4 Critical Point Detection 2075.5 Straight-Line Fitting 2115.6 Cubic Spline Fitting 2165.7 Morphology and Topology of Line Patterns 2206 Analysis of Point Patterns 2316.1 The Voronoi Diagram of Point Patterns 2326.2 Spatial Statistics of Point Patterns: Distribution Functions 2386.3 Topology and Geometry of Cellular Patterns 2456.4 The k-Nearest-Neighbor (k-NN) Problem 2517 Frequency Domain Analysis 2567.1 The 2DDiscrete Fourier Transform 2587.2 Frequency Domain Filtering 2758 Program Descriptions 2838.1 Introduction 2838.2 Programs by Chapter 2838.3 Alphabetical Listing of Programs 2869 Projects 316Appendix Synopsis of Important Concepts 325A.1 The Fourier Transform: Spatial Domain Versus Frequency Domain 326A.2 Linear Systems: Impulse Response, Convolution, and Transfer Function 330A.3 Special-Purpose Filters 335A.4 The Whittaker-Shannon Sampling Theorem 337A.5 Commonly Used Data Structures 340Index 345
