COLOR SEGMENTATION VIA IMPROVED MOUNTAIN CLUSTERING TECHNIQUE
2007 ◽
Vol 07
(02)
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pp. 407-426
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This paper proposes a new improved mountain clustering technique, which is compared with some of the existing techniques such as K-Means, FCM, EM and Modified Mountain Clustering. The performance of all these clustering techniques towards color image segmentation is compared in terms of cluster entropy as a measure of information and observed via computational complexity. The cluster entropy is heuristically determined, but is found to be effective in forming correct clusters as verified by visual assessment.
2010 ◽
Vol 36
(6)
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pp. 807-816
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Keyword(s):
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