Edge grouping around a fixation point

Toshiro Kubota
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引用次数: 2

Abstract

The paper presents three edge grouping algorithms for finding a closed contour starting from a selected edge point and enclosing a fixation point. The algorithms search a shortest simple cycle in a graph derived from an edge image where a vertex is an end point of a contour fragment and an undirected arc is drawn between every pair of end-points whose visual angle from the fixation point is less than a threshold value (set to π/2 in our experiments). The first algorithm restricts the search space to shapes where no contour point seen from the fixation point is occluded by other contour points, and finds the shortest simply cycle. The second algorithm restricts the search space to shapes where the starting edge point neither occludes nor is occluded by other contour points, and finds a shortest simple cycle. The third algorithm is free from any constraints, but does not guarantee that the solution is a shortest cycle. The third algorithm, however, guarantees a solution no worse than that of the second algorithm. The paper demonstrates effectiveness of these algorithms with a number of natural images. Finally, the paper proposes a way to automate placement of a fixation point and a starting point so that the procedure runs in a fully automated manner.
围绕注视点的边分组
本文提出了从选定的边缘点出发并包围一个不动点的封闭轮廓的三种边缘分组算法。该算法在从边缘图像导出的图中搜索最短的简单循环,其中顶点是轮廓片段的端点,并且在从固定点的视角小于阈值(在我们的实验中设置为π/2)的每对端点之间绘制无向弧。第一种算法将搜索空间限制在注视点所看到的轮廓点不被其他轮廓点遮挡的形状上,并寻找最短的简单周期。第二种算法将搜索空间限制在起始边缘点既不遮挡其他轮廓点又不遮挡其他轮廓点的形状上,并找到最短的简单周期。第三种算法不受任何约束,但不保证解是最短周期。然而,第三种算法保证的解不会比第二种算法差。本文用大量的自然图像验证了这些算法的有效性。最后,本文提出了一种自动放置固定点和起点的方法,使该过程以完全自动化的方式运行。
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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