A threshold segmentation method based on fuzzy C-means clustering algorithm and multi-histogram

Image threshholding techniques are the important content of image segmentation, one typical algorithm of which is Fuzzy C-Means (FCM) clustering segmentation algorithm. The conventional FCM clustering algorithm is based only on special information and ignores the spatial distribution of pixels in an image. Large numbers of improved methods are put forward to overcome this limitation, but all of them increased the computation cost. A new method based on FCM algorithm and multi-histogram (MHFCM) is proposed in this paper, which utilizes the special and spatial information adequately by analyzing many kinds of characteristics among different intensity levels in an image. The importing of Multi-characteristic makes the selection of thresholds possible and easy. Experimental results prove that this method can improve the segmentation effects obviously and decrease the computation cost greatly.