Practical Algorithms for Image Analysis with CD-ROM: Description, Examples, and CodeThis book offers guided access to a collection of algorithms for the digital manipulation and analysis of images. Written in classic "cookbook" style, it reflects the authors' long experience as users and developers of image analysis algorithms and software. For each task, they present a description and implementation of the most suitable procedure in easy-to-use form. The algorithms range from the simplest steps to advanced functions not commonly available for Windows users. Each self-contained section treats a single operation (histogram evaluation, low-pass filtering, and edge detection, among others). The coverage includes typical situations requiring that operation and then discusses the algorithm and implementation. Sections start with a header illustrating the nature of the procedure through a "before" and "after" pictorial example and a ready-reference that lists typical applications, keywords, and related procedures. Annotated references can be found at the end of each section. An accompanying CD-ROM contains a collection of C programs for carrying out the book's procedures. |
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addition algorithm analysis application approach approximation ARGUMENTS average background binary boundary color common computational connected construct containing contour contrast convolution coordinates corresponding curvature curve default defined described detection determine direction discussed display distance domain edge element enhancement evaluation example Figure filter Fourier frequency frequency domain function further given global histogram illustrated image filename TIF implementation indicates inimg input image intensity interest introduced iterations length low-pass matching measure methods module neighbors noise object operations OPTIONS original output image parameters pattern peak performed pixels points polygonal print Software License procedure processing produces Program provides range reduction References region Related representation represents requires respect result sampling Section segment shape shows signal simple single smoothing spatial specified spectrum step structure subsampling thinning threshold transform Typical USAGE vertical Voronoi yields