Abstract
The edge part and noise of the fuzzy image have great uncertainty, the traditional fuzzy image region segmentation process based on fuzzy logic only considers the uncertainty problem, resulting in ignoring the complexity and correlation of fuzzy image information feature, unable to realize the fuzzy image segmentation efficiently (the paper is focus on how to achieve effective separation), a fuzzy image region segmentation method based on non-robust feature fitting is proposed, to analyze the disadvantages of traditional methods, and fit the non-robust features in the fuzzy image, based on the fitting results of non-robust feature, the optimal cluster number, clustering center and other parameters of the pixel are determined by fuzzy C mean clustering method, on the basis of pixels membership function to segment fuzzy image region. Through regional texture feature, spatial location feature, regional feature color and region shape character to describe the segmentation regions, so as to preserve the segmentation results, and provide basis for future fuzzy image region segmentation. The simulation results show that the proposed segmentation method has high accuracy, and a strong practical value.
Keywords: Fuzzy image, non robust feature, region, segmentation.
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