3 results for “Markov Random Field (MRF)”

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Research ArticleOpen accessIn the keywordsA New Modified Gaussian Mixture Model for Color-Texture SegmentationM. Sujaritha, S. AnnaduraiProblem statement: This study presents a new, simple and efficient modified Gaussian mixture model based clustering algorithm for color-texture segmentation. The proposed mixture model introduces a new component density function which incorporates spatial information and the weighting factor for neighborhood effect is fully adaptive to the image content. Approach: It enhances the smoothness towards piecewise-homogeneous segmentation and reduces the edge-blurring … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,329 accessesView PDF Cite

Research ArticleOpen accessIn the abstractUnsupervised Cosegmentation Model based on Saliency Detection and Optimized Hue Saturation Value Features of SuperpixelsRasha Shoitan, Mona M. MoussaSegmenting out the foreground from a single image remains a challenge in computer vision. Image co-segmentation has been used recently to alleviate the single image segmentation by exploiting the information of the common object to be segmented from a group of images having the same object. This research proposes an unsupervised co-segmentation technique based on saliency detection and optimized features … …Journal of Computer Science, Vol. 17, Issue 7 · 3 Aug 2021 · 7,003 accessesView PDF Cite

Research ArticleOpen accessIn the abstractRange Image Segmentation by Randomized Region Growing and Bayesian Edge RegularizationSmaine Mazouzi, Mohamed BatoucheWe presented and evaluated a new Bayesian method for range image segmentation. The method proceeds in to stages. First, an initial segmentation was produced by a randomized region growing technique. The produced segmentation was considered as a degraded version of the ideal segmentation, which should be then refined. In the second stage, image pixels not labeled in the first stage … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 6,924 accessesView PDF Cite