Simulated annealing for texture segmentation with Markov models
Yalabik, M.Cemal, Yalabik Nese
Publ by IEEE, Piscataway, NJ, United States
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/27834
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.
- Conference Paper