基于阈值优化的图像模糊边缘检测算法

Fuzzy edge detection based on threshold optimization

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。

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.