并行三维12次迭代细化算法

Kálmán Palágyi , Attila Kuba
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引用次数: 212

摘要

二值图像的细化是一层又一层的迭代侵蚀,直到只剩下物体的“骨架”。提出了一种从三维二进制对象中生成曲线骨架或曲面骨架的并行细化算法。直接提取曲线骨架(即,不创建表面骨架)是很重要的。所使用的策略称为定向:每个迭代步骤由许多子迭代组成,每个子迭代都可以并行执行。该算法的一个迭代步骤包含12个子迭代,而不是通常的6个子迭代。该算法使易于实现成为可能,因为可删除点是由3×3×3匹配模板给出的。证明了(26,6)二值图的拓扑正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Parallel 3D 12-Subiteration Thinning Algorithm

Thinning on binary images is an iterative layer by layer erosion until only the “skeletons” of the objects are left. This paper presents an efficient parallel thinning algorithm which produces either curve skeletons or surface skeletons from 3D binary objects. It is important that a curve skeleton is extracted directly (i.e., without creating a surface skeleton). The strategy which is used is called directional: each iteration step is composed of a number of subiterations each of which can be executed in parallel. One iteration step of the proposed algorithm contains 12 subiterations instead of the usual six. The algorithm makes easy implementation possible, since deletable points are given by 3×3×3 matching templates. The topological correctness for (26, 6) binary pictures is proved.

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