This paper describes a new approach for the segmentation of characters in images on Web pages. In common with the authors’ previous work in this subject, this approach attempts to emulate the ability of humans to differentiate between colours. In this case, pixels of similar colour are first grouped using a colour distance defined in a perceptually uniform colour space (as opposed to the commonly used RGB). The resulting colour connected components are then grouped to form larger (character-like) regions with the aid of a fuzzy propinquity measure. This measure expresses the likelihood for merging two components based on two features. The first feature is the colour distance in the L*a*b* colour space. The second feature expresses the topological relationship of two components. The results of the method indicate a better performance than the previous method devised by the authors and comparable (possibly better) performance to other existing methods.
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机译：本文介绍了一种用于对网页图像中的字符进行分割的新方法。与作者先前在该主题中所做的工作一样，这种方法试图模仿人类区分颜色的能力。在这种情况下，首先使用在感知上均匀的颜色空间（与常用的RGB相反）中定义的色距对相似颜色的像素进行分组。然后，通过模糊的临近度度量，将所得的颜色连接的分量分组以形成较大的（字符状）区域。该度量表示基于两个特征合并两个组件的可能性。第一个特征是L * a * b *颜色空间中的颜色距离。第二个特征表示两个组件的拓扑关系。该方法的结果表明其性能优于作者设计的先前方法，并且性能可与其他现有方法媲美（可能更好）。
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