Advanced Algorithm Partitioning of Markov and Color Image Segmentation
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Date
2010
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
The color vision systems require a first step of classifying pixels in a given image into a discrete set of color classes. In this paper we introduce a new method of algorithm partitioning, and color image segmentation based on similarities or dissimilarities of the pixels. We consider fuzzy segmentation with markov, and normalized cut method. Experiments show these different processes used an effective solution on natural images, and computational efficiency. Finally, the algorithm has proven our process of experiments on gray scale, color, and texture images show promising segmentation results successful
Description
Keywords
Fuzzylmage, Markov, Normalizedcut, Segmentation, Similarities.
Citation
Toure, M. L., Beiji, Z., & Musau, F. (2010). Advanced Algorithm Partitioning of Markov and Color Image Segmentation. IEEE Xplore, 719–720.