【摘要】 针对传统的边缘检测算法对噪声敏感且伪边缘较多，提出一种基于分形特征和阈值分析的图像边缘检测方法。该方法利用改进的毯覆盖算法计算出图像的分形特征，将图像的灰度分布映射到分形维数空间上，再根据提取的分形特征图进行阈值分析，获得高低两个阈值，将像素值分为非边缘、弱边缘和强边缘3类，再对弱边缘像素进一步加以判断。实验结果与其他算法相比较表明，该算法检测出来的图像边缘伪边缘和噪声最少。更多还原

【Abstract】 Traditional edge detection algorithms are sensitive to noise and have many false edges. This paper proposes an image edge detection method based on fractal features and threshold analysis. The improved blanket coverage algorithm was used to calculate the fractal features of the image, and the gray distribution of the image was mapped to the fractal dimension space. The threshold analysis was carried out according to the extracted fractal feature image to obtain the high and low thresholds. All the pixel values were divided into three categories: non-edge, weak-edge, and strong-edge, and the weak edge pixels were further judged. Compared with other algorithms, the experimental results show that the proposed algorithm can detect the image edge completely with the least false edge and noise.更多还原