摘要
基于人工蚁群的红外图像分割方法利用模糊非线性增强算子作为启发信息,与信息素共同指导蚂蚁的行为。通过蚂蚁行走路径上的信息素分布进行更新,使得分布在目标路径上的信息素逐渐增大,逐渐向分割图像收敛,最后根据信息素分布提取分割结果。仿真和实验表明,该算法对真实图像得到了理想的分割结果。
An ant colony algorithm is presented for infrared image segmentation.The core idea is to use the fuzzy membership function as enlightening information,which guides the ant colony with the pheromone together.By updating the distribution of pheromones on the routes that the ants have passed,the pheromones on the target route are increased,and the searching routes will converge on the segmented image progressively.Finally,the segmentation results can be extracted according to the intensity of the pheromones.Simulations and experiments show that the infrared image can be segmented well.
出处
《强激光与粒子束》
EI
CAS
CSCD
北大核心
2010年第5期1005-1008,共4页
High Power Laser and Particle Beams
基金
国家部委预研资助项目(41101050102)
关键词
图像处理
信息素
红外图像
图像分割
蚁群算法
image processing
information
infrared image
image segmentation
ant colony algorithms
