对等体组、邻居组和边缘检测

R. Munasinghe, A. Davari
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引用次数: 1

摘要

标准的边缘检测器(如Canny边缘检测器)使用局部梯度算子来查找数字图像中的脊。本文提出了一种新的度量方法——对等群和邻居群,可以用来提高梯度算子的性能。阈值附近的一些像素是图像中物体较弱的边缘像素,而另一些则是由于背景不均匀而产生的不重要边缘。我们发现,使用这些边缘像素的对等组和邻居组可以比使用单个刚性阈值做出更好的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Peer groups, neighbor groups, and edge detection
Standard edge detectors such as Canny edge detector use a local gradient operator to find the ridges in digital images. In this study we show that peer groups and neighbor groups, a new measure introduced in this paper, can be used to improve the performance of gradient operators. Some of the pixels near the threshold are weaker edge pixels of the objects in the image and others are unimportant edges created by unevenness of the background. We find that peer groups and neighbor groups of these marginal pixels can be used to make a better decision regarding them than using a single rigid threshold value.
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