Abstract: 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 convergence speed, has good real-time ability, and its segmentation effect is very well.

Key words: Clonal Selection Algorithm（CSA）, coevolution, image segmentation, Otsu

摘要： 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。

关键词: 克隆选择算法, 协同进化, 图像分割, Otsu