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Improved Canny-based algorithm for image edge detection

机译:改进的基于Canny的图像边缘检测算法

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摘要

Edge detection is one of the most central branches in the field of image processing. The traditional edge detection algorithm is studied for its poor resistance to pretzel noise and poor adaptability of threshold selection. An improved image edge detection algorithm based on Canny is proposed, which firstly combines improved adaptive median filtering to reduce image noise. Then, the local adaptive thresholds are used to detect the edges of the image. The comparison of experimental results shows that the improved algorithm, which addresses the shortcomings of the traditional Canny algorithm, is better at removing the interference of pepper noise and preserving the image edge details.
机译:边缘检测是图像处理领域中最中心的分支之一。 研究了传统的边缘检测算法,对其对椒盐振噪声的耐受性差和阈值选择的适应性差。 提出了一种改进的基于Canny的图像边缘检测算法,其首先结合了改进的自适应中值滤波以降低图像噪声。 然后,局部自适应阈值用于检测图像的边缘。 实验结果的比较表明,一种改进的算法,解决了传统罐装算法的缺点,更好地消除了胡椒噪声的干扰并保持图像边缘细节。

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