基于LoG算法的自适应边缘检测方法

Sifeng Wang, Jingxiu Zhao
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引用次数: 2

摘要

分析了LoG算子的边缘检测能力,提出了LoG算子在实际应用中存在的不足。为了避免LoG算子的缺陷,本文根据实验数据和Matlab软件推导出灰度共生矩阵的熵与高斯空间系数的关系。基于具体图像的熵,可以自适应获取LoG算子的最优高斯空间系数。因此,本文改进的方法既能有效地控制图像中的大部分噪声,又能准确地定位图像的边缘。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A self-adaptive edge detection method based on LoG algorithm
The capability of edge detection using LoG operator is analyzed in this paper and the paper proposes the deficiency of the LoG operator in the practical application. In order to avoid the defects of the LoG operator, the paper based on the date of experimentation and the Matlab software elicits the relation between the entropy of the gray level co-occurrence matrix and the Gassian space coefficient. Optimum Gassian space coefficient of LoG operator can be self-adaptive acquired based on the entropy of the concrete image. So the methods improved in the paper not only effectively control the most noise of the image, but also locate the edge accurately.
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