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Edge Grouping Around a Fixation Point

机译:边缘分组在固定点周围

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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.
机译:本文呈现了三个边缘分组算法,用于从选定的边缘点找到闭合轮廓并封闭固定点。该算法在从边缘图像导出的图表中搜索最短的简单周期,其中顶点是轮廓片段的终点,并且在每个对视角来自定影点的视角小于a的一对终点点之间绘制的无向弧。阈值(在我们的实验中设置为π/ 2)。第一算法将搜索空间限制为形状,其中从固定点看不到的轮廓点被其他轮廓点封闭,并且找到最短的简单循环。第二算法将搜索空间限制为形状,其中起始边缘点既不被遮挡也不被其他轮廓点遮挡,并且找到最短的简单周期。第三种算法没有任何约束,但不保证解决方案是最短的循环。然而,第三算法保证了不比第二算法的解决方案。本文展示了这些算法与许多自然图像的有效性。最后,本文提出了一种自动放置固定点和起点的方法,使得过程以完全自动化的方式运行。

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