Abstract
A new image segmentation algorithm based on the fusion of Markov random field and fuzzy c-means clustering (FCM) is proposed in this paper. Due to disregard of spatial constraint information, the FCM algorithm fails to segment images corrupted by noises. For improving the robustness of FCM to noises, we use Markov random field model to represent the spatial constraint information of an image and based on the fusion of Markov spatial constraint field and the fuzzy segmentation information resulting from FCM, the new algorithm overcomes the problem of FCM and keeps the computation simplicity. The results of experiments prove the robustness and validity our algorithm.
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