在多种字体大小的文档中,独立于脚本的粗体字检测

P. Saikrishna, A. Ramakrishnan
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引用次数: 2

摘要

提出了一种与文字无关、字体大小无关的打印页面粗体字检测方案。在OCR应用程序中,例如对现有打印表单进行微小修改,需要在OCR识别的文档中重现字体大小和特征,例如粗体和斜体。在基于形态学开度的黑体检测(MOBDoB)方法中,利用词高信息将二值化后的图像分割成具有统一字体大小的子图像。从密度中得到各子图像中字符笔画宽度的粗略估计。然后用正方形结构元素打开每个子图像,其大小由各自的笔画宽度决定。所有打开的子图像的并集用于确定加粗单词的位置。从二值化后的图像中提取所有这些词就得到了最终的图像。从总共65个泰米尔语、卡纳达语和英语页面中,至少检测出98%的粗体单词,误报率低于0.4%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Script independent detection of bold words in multi font-size documents
A script independent, font-size independent scheme is proposed for detecting bold words in printed pages. In OCR applications such as minor modifications of an existing printed form, it is desirable to reproduce the font size and characteristics such as bold, and italics in the OCR recognized document. In this morphological opening based detection of bold (MOBDoB) method, the binarized image is segmented into sub-images with uniform font sizes, using the word height information. Rough estimation of the stroke widths of characters in each sub-image is obtained from the density. Each sub-image is then opened with a square structuring element of size determined by the respective stroke width. The union of all the opened sub-images is used to determine the locations of the bold words. Extracting all such words from the binarized image gives the final image. A minimum of 98 % of bold words were detected from a total of 65 Tamil, Kannada and English pages and the false alarm rate is less than 0.4 %.
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