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Analysis of Merge Criteria within a Watershed Based Segmentation Algorithm

机译:基于流域的分割算法中的合并标准分析

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The watershed transform is a very powerful segmentation tool which guarantees closed contours. In this paper the watershed transform is used for the segmentation of a very simple image consisting of a circle, a rectangle and a background region. The ability of different merge criteria to find these major structures based on the highly over-segmented watershed transform for different signal to noise ratios (SNR) is analyzed. Special focus is given to the compensation of prior merge probabilities induced by the topology of the over-segmented watershed images. Herby a relative performance increase of 5.1% to 23.5% is achieved for the different merge criteria.
机译:流域变换是一个非常强大的分割工具,可确保封闭的轮廓。在本文中,流域变换用于分割由圆,矩形和背景区域组成的非常简单的图像。分析了不同合并标准的能力,以基于高度过度分段的流域变换用于不同信号与噪声比(SNR)的高度分段的流域变换。特别焦点通过过分分割的流域图像的拓扑诱导的先前合并概率的补偿。对于不同的合并标准,达到了5.1%至23.5%的相对性能增加了5.1%至23.5%。

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