一种快速精确的欧氏距离变换算法

Shuang Chen, Junli Li, Xiuying Wang
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引用次数: 5

摘要

欧氏距离变换广泛应用于图像分析和处理的许多领域。传统算法耗时长,实现难度大。提出了一种新的快速距离变换算法。首先在行和列中标记出每个前景最近的背景像素的位置,然后利用标记扫描前景区域,计算出第一个前景像素的距离变换信息,根据第一个像素的信息,为其相邻的4个前景像素设计4个小区域,并根据标记搜索出每个相邻前景像素最近的背景像素。随着区域的增长,迭代处理每个相邻像素,直到所有前景像素被解决。该算法效率高,实现简单。实验表明,与现有的边界条带化和轮廓跟踪算法相比,该算法在时间和空间消耗方面都有显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Fast Exact Euclidean Distance Transform Algorithm
Euclidean distance transform is widely used in many applications of image analysis and processing. Traditional algorithms are time-consuming and difficult to realize. This paper proposes a novel fast distance transform algorithm. Firstly, mark each foreground's nearest background pixel's position in the row and column, and then use the marks scan the foreground area and figure out the first foreground pixel distance transform information, According to the first pixel' information, design four small regions for its 4-adjacent foreground pixel and also based on the marks search out each adjacent foreground pixel's nearest background pixel. As the region growing, iteratively process each adjacent pixel until all the foreground pixels been resolved. Our algorithm has high efficiency and is simple to implement. Experiments show that comparing to the existing boundary striping and contour tracking algorithm, our algorithm demonstrates a significant improvement in time and space consumption.
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