Fuzzy C-Means Clustering for Image Segmentation Using the Adaptive Spatially Median Neighborhood Information

The application of fuzzy c-means algorithm to image segmentation is not taking into account spatial information apart from intensity values , which will lead a misclassification on the boundaries and inhomogeneous regions with noises.In order to solve this problem, a new image segmentation method is proposed using adaptive spatially median neighborhood information and fuzzy c-means algorithm in this paper. First, an adaptive spatial information function is defined to exploit the spatial information,which is not only effective to deal with noisy, but also reserve well edge property; Second, it designs the neighbourhood information weighted membership matrix with spatial contraints and proves this weighted membership matrix to satisfy two norms of polarity and spatial continuity;Finally, by application of this algorithm to synthetic image and brain imag segmentation. The experimental results show the proposed segmentation scheme that is proved effective for noisy image and at the same time it distinguishes itself by higher correct classification ratio .