基于Canny算子的自适应图像边缘检测算法

Liying Yuan, Xue Xu
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引用次数: 80

摘要

针对单一边缘检测方法导致的梯度变化较重和较弱的边缘缺失问题,本文采用全局边缘检测与局部边缘检测相结合的方法提取边缘。采用基于Canny算子的自适应平滑滤波算法进行全局边缘检测,获得整个边缘。与Canny算子和Sobel算子的边缘检测效果相比,改进Canny算子的边缘检测效果是最完整、最丰富的,不包含假边缘。针对整体检测无法得到边缘的情况,本文选择局部检测方法进行边缘提取。局部边缘检测采用基于k-平均方法的距离加权平均方法,可以有效克服异常点对聚类的影响。采用全局与局部相结合的边缘检测方法,得到完整的颅骨图像边缘。与Canny边缘检测方法相比,该算法能有效提取图像边缘,并具有较强的抗噪能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Image Edge Detection Algorithm Based on Canny Operator
For single edge detection methods causing important and weak gradient change edge missing problems, this paper adopts the method of combining global with local edge detection to extract edge. The global edge detection can obtain the whole edge, which uses adaptive smooth filter algorithm based on Canny operator. Compared with effect of edge detection from the Canny operator and Sobel operator, the edge from improved Canny operator is the most complete and rich, do not contain false edge. To the whole detection failed to get the edge, the paper selects local area detection method for edge extraction. Local edge detection which uses distance weighted average method based on k-average method can overcome the impact of outliers on clustering effectively. Complete skull image edge is got through edge detection method that combines global with local. Compared with the Canny edge detection method, this algorithm can extract image edge effectively, and have the powerful anti-noise ability.
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