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Titlebook: Information Theory in Computer Vision and Pattern Recognition; Francisco Escolano,Pablo Suau,Boyán Bonev Textbook 2009 Springer-Verlag Lon

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Textbook 2009ering and segmentation, saliency detection, feature selection, optimal classifier design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information…), principles (maximum entropy, min
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Contour and Region-Based Image Segmentation, background, or by finding the optimal partition of the image into its constituent parts. Here . means that pixels (or blocks in the case of textures) in the foreground region share common statistics. These statistics should be significantly different from those corresponding to the background. In t
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Registration, Matching, and Recognition,. Registration is defined as the task of finding the minimal amount of transformation needed to transform one pattern into another (as much as possible). The computational solution to this problem must be adapted to the kind of patterns and to the kind of transformations allowed, depending on the do
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