关键词: 图像分割, 模糊C-均值聚类, 多链拓展编码, 人工蜂群算法

Abstract: In order to solve the defects of the conventional Fuzzy C-Means（FCM） clustering algorithm which is sensitive to the selection of initial values and noise data, this paper proposes an algorithm of Fuzzy C-Means clustering based on Multi-chain Quantum Bee Colony algorithm（MQBC-FCM）, Firstly, it introduces the expanded multi-chains coding method to the Quantum Artificial Bee Colony（QBC） algorithm and proposes the MQBC algorithm. Then it applies the MQBC algorithm to search for the optimal initial clustering centers. In the end, it designs a new image segmentation method based on multi-chain quantum bee colony algorithm optimizing fuzzy C-means clustering centers. The experimental results show that MQBC-FCM is efficient and the proposed method performs better in segmentation accuracy, time complexity and robustness than the image segmentation algorithms of FCM and fuzzy-based ABC.

Key words: image segmentation, fuzzy C-means clustering, expansion of multi-chain coding, artificial bee colony algorithm