摘要
图像的边缘检测是图像预处理的重要内容之一，它是对图像进行视觉分析和模式识别的基本前提。利用遗传算法对最大类间方差法进行优化，自动确定图像分割最佳分割阈值即图像增强的渡越点值，并简化隶属度函数，采用“Max”算子和“Min”算子相结合方法改进了传统单一算子的边缘检测方法。仿真实验表明，该算法不仅能提高图像模糊边缘检测能力，而且能够有效的降低图像模糊和噪声对边缘检测的干扰。
The image edge detection is a crucial part of image processing, which is a prerequisite of visual analysis and pattern recognition. The maximum class variance method can be improved by genetic algorithm the transition dot value of the image fuzzy enhancement automatically come out and the membership ship functions can be simplified. The single operator of traditional edge detection method can be modified with the combination of the max and the min operators. Simulation results show this algorithm can not only improve the image fuzzy edge detection but also can reduce the noise of interference.
关键词
遗传算法
最大类间方差法
模糊增强
边缘检测
genetic algorithm
maximum class variance
method
fuzzy enhancement
edge detection
