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Clustering based segmentation of text in complex color images

机译:基于聚类的复杂彩色图像中的文本分割

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摘要

We propose a novel scheme based on clustering analysis in color space to solve text segmentation in complex color images. Text segmentation includes automatic clustering of color space and foreground image generation. Two methods are also proposed for automatic clustering: The first one is to determine the optimal number of clusters and the second one is the fuzzy competitively clustering method based on competitively learning techniques. Essential foreground images obtained from any of the color clusters are combined into foreground images. Further performance analysis reveals the advantages of the proposed methods.
机译:我们提出了一种基于颜色空间中聚类分析的新方案,以解决复杂彩色图像中的文本分割问题。文本分割包括颜色空间的自动聚类和前景图像生成。还提出了两种自动聚类方法:第一种是确定最佳聚类数,第二种是基于竞争学习技术的模糊竞争聚类方法。从任何颜色群集获得的基本前景图像都将合并为前景图像。进一步的性能分析揭示了所提出方法的优点。

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