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A Multiple Classifier Approach for the Recognition of Screen-Rendered Text

机译:屏幕呈现文本识别的多分类器方法

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摘要

The lower the resolution of a given text is, the more difficult it becomes to segment and to recognize it. The resolution of screen-rendered text can be very low. With a typical x-height of 4 to 7 pixels it is much lower as in other low resolution OCR situations. Modern OCR approaches for such very low resolution text use a classification-based segmentation where the underlying classifier plays an important role. This paper presents a multiple classifier system for the classification of single characters. This system is used as a subsystem for the classification-based segmentation within a system to read screen-rendered text. The paper shows that the presented multiple classifier system outperforms the best former single classifier system on single characters by far and it shows the impact of using the multiple classifier system on the word reading performance.
机译:给定文本的分辨率越低,对其进行分割和识别就越困难。屏幕渲染文本的分辨率可能会很低。典型的x高度为4到7像素,它比其他低分辨率OCR情况低得多。对于此类分辨率极低的文本,现代OCR方法使用基于分类的细分,其中基础分类器扮演着重要角色。本文提出了一种用于单个字符分类的多重分类器系统。该系统用作系统中基于分类的细分的子系统,以读取屏幕呈现的文本。论文表明,所提出的多重分类器系统在单个字符上的性能远远优于以前最好的单一分类器系统,并且表明了使用多重分类器系统对单词阅读性能的影响。

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