An efficient fully parallel thinning algorithm

N.H. Han, C. La, P. Rhee
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引用次数: 30

Abstract

The paper addresses an efficient parallel thinning algorithm based on weight-values. The weight-value of a black pixel is calculated by observing neighboring pixels, and it gives one an efficient way to decide whether the pixel is deleted or not. Owing to weight-values, the proposed algorithm uses only 3/spl times/3 templates. Furthermore, it examines only the elimination conditions corresponding the weight-value of boundary pixels, and all elimination conditions will not be searched as most other parallel iterative thinning algorithms. Thus, the execution time can be reduced a lot compared to that of previous approaches. The weight-value also allow one to deal with typical troublesome patterns efficiently. Without smoothing before thinning, the algorithm produces robust thinned images even in the presence of two pixel-width noises. The authors obtain encouraging results from extensive experiments.
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一种高效的全并行细化算法
提出了一种基于权值的并行细化算法。通过观察相邻像素来计算黑色像素的权重值,为判断该像素是否被删除提供了一种有效的方法。由于权重值的存在,该算法只使用了3/spl次/3个模板。此外,它只检查边界像素权值对应的消除条件,而不像大多数其他并行迭代细化算法那样搜索所有消除条件。因此,与以前的方法相比,执行时间可以减少很多。权重值还允许有效地处理典型的麻烦模式。该算法无需在细化前进行平滑处理,即使存在两个像素宽度的噪声,也能产生鲁棒的细化图像。作者从大量的实验中获得了令人鼓舞的结果。
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