关键词: 马尔科夫随机场, 图像分割, 模糊聚类, 邻域信息, 抗噪性

Abstract:

Aiming at the problem that the utilization rate of neighborhood information and spatial information of fuzzy clustering algorithm is low and susceptible to noise, an improved Fuzzy C-Means（FCM） algorithm based on Markov random field model, namely FKMFCM algorithm, is proposed. On the basis of FCMKM algorithm, the prior probability of Markov random field is added, and the objective function of FCM algorithm is improved by using the prior probability. In order to verify the performance of FKMFCM algorithm, Bezdek partition coefficient, Xie_Beni coefficient, running time and iteration times are selected as the evaluation criteria of comparative experiments. The experimental results show that the FKMFCM algorithm can effectively improve the anti-noise performance of the fuzzy clustering algorithm.

Key words: Markov random field, image segmentation, fuzzy clustering, neighborhood information, noise resistance