Abstract: Fuzzy exponent entropy based on exponent entropy is defined and its properties is proved，avoiding the problems of logarithmic behavior.The fuzzy patition definition of an image is given by the conditional probability and the concept，automatic image segmentaion algorithm using the maximum entropy is presented.For reducing computation complexity and enhancing speed，the paper designs self-adaptive similartaxis operator and random dissimilation operator with small probability.The improved Mind Evolutionary Algorithm（MEA） optimizes the fuzzy parameters and searches the optimal threshold value for image segmentation.The experimental results show that the proposed method can select the threshold values automatically and efficiently，better than Otsu and other two methods.

摘要： 在指数熵的基础上给出了模糊指数信息熵的定义及其性质，避免了对数中无定义点的问题，并用此概念和条件概率定义图像模糊划分的熵，根据熵最大原理进行图像自动分割。为了降低计算复杂度，提高计算速度，改进了思维进化算法（MEA），设计了自适应趋同和小概率随机异化操作，优化模糊隶属参数，搜索最优分割阈值。实验结果表明，该方法能够自动、有效地选取阈值，分割效果优于Otsu等其他算法，并能保留原始图像的主要特征。