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Unsupervised texture segmentation using stochastic version of the EM algorithm and data fusion

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1 Author(s)
Cruz, C.A. ; Dept. de Electr., Univ. Autonoma Metropolitana, San Pablo, Mexico

In this paper I present a new methodology for texture segmentation. This methodology is based through the high order statistics features, the data fusion techniques and finally though the maximum likelihood method in order to find the clusters. The methodology is applied in order to segment natural micro-textures

Published in:

Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on  (Volume:2 )

Date of Conference:

16-20 Aug 1998