A Thinning-free Algorithm for Straight Edge Detection in a Gray-scale Image

Sanjoy Pratihar, Partha Bhowmick
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引用次数: 11

Abstract

An efficient algorithm to detect the straight edges present in a gray-scale image is proposed.Algorithms to detect curvilinear edges (of possibly uneven thickness) and algorithms to segment a one-pixel thick digital curve into a sequence of straight pieces are found in the literature in several varieties and in several paradigms. However, to the best of our knowledge, there exists no algorithm till date that can detect straight edges in a gray-scale image without thinning. The proposed algorithm uses the novel idea of exponential averaging to achieve a carry-forward of previous edge strengths along the traversed straight edge. The process is computationally attractive, since the underlying operations at an edge point effectively reduce to one right shift and one integer addition. The straightness of an edge is verified from classical chain code properties realizable by simple integer operations, thereby making the algorithm easy for implementation and fast in execution. Experimental results demonstrate its efficiency and robustness.
灰度图像直线边缘检测的无稀疏算法
提出了一种检测灰度图像中直线边缘的有效算法。检测曲线边缘(可能厚度不均匀)的算法和将一像素厚的数字曲线分割成一系列直线片段的算法在几种变体和几种范式的文献中被发现。然而,据我们所知,迄今为止还没有一种算法可以在不细化的情况下检测灰度图像中的直线边缘。提出的算法采用指数平均的新思想,实现沿遍历的直边的先前边缘强度的延续。这个过程在计算上是有吸引力的,因为在边缘点上的底层操作有效地减少到一次右移和一次整数加法。通过简单的整数运算验证经典链码的直线性,从而使算法易于实现,执行速度快。实验结果证明了该方法的有效性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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