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      Simulated annealing for texture segmentation with Markov models

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      Author
      Yalabık, M. Cemal
      Yalabık, N.
      Date
      1989
      Source Title
      Proceedings of the International Workshop on Industrial Applications of Machine Intelligence and Vision, MIV 1989
      Publisher
      IEEE
      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.
      Keywords
      Markov models
      Simulated annealing
      Texture segmentation
      Image processing
      Permalink
      http://hdl.handle.net/11693/27834
      Published Version (Please cite this version)
      http://doi.org/10.1109/MIV.1989.40535
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      • Department of Physics 2299
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