Image Segmentation Based on Fuzzy Clustering Algorithm

نویسندگان

  • Chaur-Heh Hsieh
  • Chung Ming Kuo
  • Chung-Woei Chao
  • Po-Chiang Lu
چکیده

Image segmentation plays an important role for machine vision applications. In this paper, we present a new segmentation strategy based on fuzzy clustering algorithm. The new algorithm includes the spatial interactions by assuming that the statistical model of segmented image regions is Gibbs Random Field ( GRF ). We specitjl the neighborhood system, the associated cliques. and the potentials of the GRF. Then, we redefine the objective hnction of Fuzzy C-Means ( FCM ) clustering algorithm to include the energy function that is the sum of potentials. The modified membership equation is derived. By including the modified membership equation in the modified FCM clustering algorithm, the segmentation is achieved. Experiment results show that the new algorithm yields better segmentation results. Moreover, it is faster than the conventional adaptive segmentation algorithm.

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تاریخ انتشار 1994