Image Processing, Analysis, and Machine VisionThompson Learning, 2008 - 829 sidor This robust text provides deep and wide coverage of the full range of topics encountered in the field of image processing and machine vision. As a result, it can serve undergraduates, graduates, researchers, and professionals looking for a readable reference. The book's encyclopedic coverage of topics is wide, and it can be used in more than one course (both image processing and machine vision classes). In addition, while advanced mathematics is not needed to understand basic concepts (making this a good choice for undergraduates), rigorous mathematical coverage is included for more advanced readers. It is also distinguished by its easy-to-understand algorithm descriptions of difficult concepts, and a wealth of carefully selected problems and examples. |
Innehåll
The image its representations and properties | 11 |
The image its mathematical and physical background | 49 |
Data structures for image analysis | 98 |
Upphovsrätt | |
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algorithm Analysis and Machine applications approach binary boundary brightness camera classifier co-ordinates coefficients color complex compression Computer Vision considered constraint contour convex convex hull corresponding cost curve defined derived described direction discrete distance distance transform edge detection element equation estimate evaluation example filter Fourier transform frequency function fuzzy fuzzy set Gaussian geometric global gradient graph gray-level gray-scale histogram Hough transform IEEE IEEE Transactions image data Image Processing image segmentation image understanding input intensity iterations labeling linear Machine Intelligence Machine Vision matching mathematical morphology matrix Medical Imaging methods motion neighborhood node noise object optical flow optimal original image parameters Pattern Analysis Pattern Recognition pixel points primitives problem properties quadtree reconstruction region represent representation sampling scene Section sequence shape space spatial step surface syntactic techniques texture description texture primitives threshold training set Transactions on Pattern vector voxel wavelet