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Text Detection on Charts and Graphs

机译:图表上的文本检测

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摘要

Current Optical Character Recognition (OCR) systems are not capable of detection and recogni- tion of detached words on an image, especially if the text is not located horizontally. Such text blocks are typ- ical of charts and graphs. In this paper an algorithm of detection of small text blocks with arbitrary orienta- tion, color, style, and font size, which can be used for text localization before application of arbitrary charac- ter recognition system, is proposed. According to the experimental results, the use of the proposed algorithm for determination of the location and orientation of text blocks on charts and graphs and the transmission of this information to text recognition system allow increasing the fullness by 20 times and the text recognition precision by 15 times. The experiments were carried out on a test collection of 1000 charts containing about 14 000 text blocks, which was created by means of the XML/SWF Chart tool.
机译:当前的光学字符识别(OCR)系统无法检测和识别图像上的分离单词,尤其是在文本不是水平放置的情况下。这种文本块是图表和图形的典型代表。本文提出了一种检测具有任意方向,颜色,样式和字体大小的小文本块的算法,该算法可在应用任意字符识别系统之前用于文本定位。根据实验结果,使用所提出的算法确定图表和图形上文本块的位置和方向,并将此信息传输到文本识别系统,可以使填充度提高20倍,文本识别精度提高15倍次。实验是在1000个图表的测试集合上进行的,其中包含大约14000个文本块,这些图表是通过XML / SWF图表工具创建的。

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