基于混合PSO-CS算法的彩色图像多阈值分割  

Multi-threshold Segmentation of Color Image Based on Hybrid PSO-CS Algorithm

作　　者：卫洪春[1] 

机构地区：[1]四川文理学院计算机学院,四川达州635000

出　　处：《计算机与现代化》2017年第8期61-65,共5页Computer and Modernization

基　　金：四川省教育厅一般项目(15ZB0326);四川文理学院特色培育项目(2015TP003Y)

摘　　要：彩色图像分割是数字图像处理的一个难点。本文研究群体智能算法对彩色图像的分割,针对布谷鸟算法莱维飞行寻优的跳跃性带来的缺陷,在每次莱维飞行结束后引入一种改进的粒子群位置变异方程引导寻优,并对发现概率和步长因子分别提出新的自适应方程,在此基础上提出一种混合粒子群布谷鸟算法(HPCS),以此混合算法进行彩色图像多阈值分割。实验结果表明,本文提出的HPCS算法在彩色图像分割的效率和质量方面均比较理想。Color image segmentation is a difficult problem in digital image processing. In this paper, the use of swarm intelligence algorithm for color image segmentation is studied. For the defect on the cuckoo algorithm caused by optimization of Levy flight jumping, after each end of Levi flight, a modified particle swarm location variation equation is introduced to guide the global opti- mal solution, and the corresponding adaptive equations are also proposed for the discovery probability and the pace factor. So a hybrid particle swarm cuckoo algorithm（HPCS） is proposed, which is used to carry on multi-threshold segmentation of color image. The experiment shows that the HPCS algorithm is good in the efficiency and quality of color image segmentation.

关 键 词：多阈值分割 粒子群算法 布谷鸟算法 混合粒子群布谷鸟算法 发现概率 步长因子 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]