树剪枝:一种新的图像自动分割算法及其与分水岭变换的对比分析

P. A. Miranda, F. Bergo, Leonardo M. Rocha, A. Falcão
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引用次数: 8

摘要

在图像森林变换(IFT)的框架中提出了使用树修剪(TP)和分水岭(WS)进行图像分割的方法。IFT是一种将与连通性相关的图像处理问题转化为图中最优路径森林问题的方法。考虑到这两种算法使用具有相似参数的IFT,它们通常产生相似的分割结果。然而,它们依赖于IFT的不同属性,这使得TP在自动分割任务中比WS更健壮。我们提出并论证了TP算法的一个重要改进,澄清了TP与WS的区别,并从理论和实践的角度对两者进行了比较分析。该实验涉及对数据库中990张图像的车牌进行自动分割
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tree-Pruning: A New Algorithm and Its Comparative Analysis with the Watershed Transform for Automatic Image Segmentation
Image segmentation using tree pruning (TP) and watershed (WS) has been presented in the framework of the image forest transform (IFT) - a method to reduce image processing problems related to connectivity into an optimum-path forest problem in a graph. Given that both algorithms use the IFT with similar parameters, they usually produce similar segmentation results. However, they rely on different properties of the IFT which make TP more robust than WS for automatic segmentation tasks. We propose and demonstrate an important improvement in the TP algorithm, clarify the differences between TP and WS, and provide their comparative analysis from the theoretical and practical points of view. The experiments involve automatic segmentation of license plates in a database with 990 images
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