Simulated annealing for texture segmentation with Markov models

Date
1989
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Source Title
Proceedings of the International Workshop on Industrial Applications of Machine Intelligence and Vision, MIV 1989
Print ISSN
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Publisher
IEEE
Volume
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Pages
118 - 123
Language
English
Type
Conference Paper
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Abstract

Binary textured images are segmented into regions of different textures. The binary Markov model is used, and model parameters are assumed to be unknown prior to segmentation. The parameters are estimated using a weighted-least-squares method, while segmentation is performed iteratively using simulated annealing. To speed up the annealing process, an initial coarse segmentation algorithm that quickly determines the approximate region categories using k-means clustering algorithm is used. The results look promising, and the computational costs can be reduced further by optimization of the computations.

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Keywords
Markov models, Simulated annealing, Texture segmentation, Image processing
Citation
Published Version (Please cite this version)