[PDF.76nl] Markov Random Fields in Image Segmentation (Foundations and Trends(r) in Signal Processing)
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Markov Random Fields in Image Segmentation (Foundations and Trends(r) in Signal Processing)
Zoltan Kato, Josiane Zerubia
[PDF.we60] Markov Random Fields in Image Segmentation (Foundations and Trends(r) in Signal Processing)
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| #5002690 in Books | Now Publishers Inc | 2012-09-26 | Original language:English | PDF # 1 | 9.21 x.36 x6.14l,.54 | File type: PDF | 168 pages | |
Markov Random Fields in Image Segmentation provides an introduction to the fundamentals of Markovian modeling in image segmentation as well as a brief overview of recent advances in the field. Segmentation is formulated within an image labeling framework, where the problem is reduced to assigning labels to pixels. In a probabilistic approach, label dependencies are modeled by Markov random fields (MRF) and an optimal labeling is determined by Bayesian estimation, in part...
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