Abstract
Image segmentation is a key process in computer vision and image process applications. Accurate segmentation of medical images is very essential in medical applications but it is very difficult job due to noise and in homogeneity that are usual of medical images. In this paper a new method, based on FCM, is proposed to make FCM more robust against noise. Multi-scale images are obtained by smoothing input image in different scales. FCM is applied to multi-scale images from high scale to low scale. First FCM is applied to image with highest scale. Then in each scale, cluster centers of previous scale are used to initialization membership for current scale. Moreover, in FCM, neighborhood attraction is used to more decrease effect of noise in clustering. Experimental result shows effectiveness of new method.
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