Abstract:

The traditional fuzzy Cmeans (FCM) clustering algorithm has some problems, such as massive calculation and slow operation speed, especially the large amount of data. A fast multithresholds FCM algorithm based on histogram correlation constraints is proposed to control the image distortion due to resampling. Because of the amount of data in the operation has been reduced,the segmentation speed turns faster. In this paper, image segmentation uses the  fuzzy techniques of the fuzzy C Means (FCM) algorithm which considers each pixel for the cluster center membership. FCM can achieve multithreshold image segmentation which features good applicability. The experimental results which make it valuable on application shows that the proposed algorithm preserves the effect and costs only 1.4% the time of the traditional FCM.

Key words: fuzzy Cmean (FCM) clustering algorithm;image segmentation;fuzzy clustering;histogram;correlation