计算机工程与应用2017，Vol.53Issue(24)：8-14,7.DOI:10.3778/j.issn.1002-8331.1710-0055
基于多链量子蜂群算法的模糊聚类图像分割
Fuzzy C-means clustering image segmentation method based on multi- chain quantum bee colony algorithm
摘要
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 meth-od 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 com-plexity and robustness than the image segmentation algorithms of FCM and fuzzy-based ABC.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Key words
image segmentation/fuzzy C-means clustering/expansion of multi-chain coding/artificial bee colony algorithm分类
信息技术与安全科学引用本文复制引用
冯玉芳,卢厚清,殷宏..基于多链量子蜂群算法的模糊聚类图像分割[J].计算机工程与应用,2017,53(24):8-14,7.基金项目
国家自然科学基金(No.71501186). （No.71501186）
