边缘检测是图像预处理中最重要的内容之一，本文使用遗传算法对阈值优化得到最佳阈值参数，对模糊边缘检测算法进行改进，根据此最佳阈值来定义一个新的简单隶属度函数，简化了Pal.King算法中复杂的G和G-1运算。不仅使复杂计算简单化，还减少了迭代次数。仿真结果表明：该算法具有较强的检测模糊边缘能力,是一种实用、高效的边缘提取算法，同时此方法很容易扩展到多阈值图像边缘处理。关键词: 边缘检测；隶属函数；模糊特征平面；模糊增强；阈值优化Fuzzy edge detection based on threshold optimization Luo yu-ling(1) (2) Tang xian-ying(1)1(Institute of Computer and Communication Engineering, Changsha University Of Science and Technology, HuNan, 410076, China) 2 (Department of Computer Science, XiangNan University Of Science and Technology, HuNan. 423000, China) Abstract：Edge detection is one of the most important elements in Image processing. This Paper makes some improvement to the Pal. King fuzzy edge-detection algorithm. This is present a scheme for optimal thresholding using genetic algorithms. A new definition of a simple membership function according to the optimal thresholding. Simplified complex G and G-1 operations of Pal. King Algorithms. This improved algorithm not only simplifies complex calculation, but also brings out a new transformation of fuzzy enhancement, and reduces the count of iterations. Simulation results show that: the algorithm is a practical and efficient edge detection algorithm, and this method can easily extend to more threshold edge detection of image processing.Keywords: edge detection；membership function；Fuzzy property domain；Fuzzy enhancement；Threshold optimization