基于免疫遗传算法的图像多阈值分割

Immune Genetic Algorithm for Multi-Level Threshold Image Segmentation

针对H.D.Cheng等人提出的模糊最大熵原则阈值分割法存在着计算量巨大的问题,将具有高效鲁棒性、自适应性、并行性的免疫遗传算法引入阈值自动选取算法中,并针对该方法的疫苗选取会导致收敛到局部最优解等问题,给出了高效的自适应疫苗选取新方法。通过实验显示了该算法在收敛性和计算效率上较其它优化算法具有更好的优越性。

There is a problem of computationally prohibitive when fuzzy c partitions maximum entropy is applied to muli-level thresh-old selection. An improved immune genetic algorithm is proposed to solve the problem. The results show that it can shorten the com-putational time compared with the simple genetic algorithm and Immune genetic algorithm.