An Automatic Image Segmentation Algorithm Based on Weighting Fuzzy C-Means Clustering
Image segmentation is an important research topic in the field of computer vision. Now the fuzzy C-Means (FCM) algorithm is one of the most frequently used clustering algorithms. Although a FCM algorithm is a clustering without supervising, the FCM arithmetic should be given the transcendent information of prototype parameter; otherwise the arithmetic will be wrong. This limits its application in image segmentation. In this paper, we develop a new theoretical approach to automatically selecting the weighting exponent in the FCM to segment the image, which is called Automatic Clustering Weighting Fuzzy C-Means Segmentation (ACWFCM). This method can reduce the disturbance of noise; get the segmentation numbers more accurately. The experimental results illustrate the effectiveness of the proposed method.
KeywordsImage segmentation Fuzzy C-Means clustering Weighting Fuzzy C-Means algorithm Clustering analysis Automatic Clustering Weighting Fuzzy C-Means Segmentation
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