基于种内协同克隆选择的Otsu图像分割算法

摘要

Traditional two-dimensional Otsu’s method has the disadvantages of high computational complexity, poor real-time performance. In order to improve its efficiency, inspired by the collaborative relationships among group members, a Clonal Selection Algorithm based on Cooperation within Species(CSACS)is proposed. CSACS is compared with Clonal Selection Algorithm(CSA), and is used to image segmentation. The experimental results show that:the algorithm can accelerate the con-vergence speed, has good real-time ability, and its segmentation effect is very well.%传统二维Otsu算法存在计算复杂度高、实时性差等缺点。针对这一不足，受生物群体成员间协作关系的启示，对克隆免疫算法进行改进，提出了一种基于种内协同的克隆选择算法（Clonal Selection Algorithm based on Cooperation within Species，CSACS），将其与克隆选择算法（Clonal Selection Algorithm，CSA）进行对比测试，将其应用于二维Otsu图像分割。测试实验表明：该算法能加快收敛速度，具有较好的实时性，且分割效果较为理想。