Keyword Spotting in Document Images through Word Shape Coding

Shuyong Bai, Linlin Li, C. Tan
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引用次数: 56

Abstract

With large databases of document images available,a method for users to find keywords in documents will be useful. One approach is to perform Optical Character Recognition (OCR) on each document followed by indexing of the resulting text. However, if the quality of the document is poor or time is critical,complete OCR of all images is infeasible. This paper build upon previous works on Word Shape Coding to propose an alternative technique and combination of feature descriptors for keyword spotting without the use of OCR. Different sequence alignment similarity measures can be used for partial or whole word matching. The proposed technique is tolerant to serifs,font styles and certain degrees of touching, broken or overlapping characters. It improves over previous works with not only better precision and lower collision rate, but more importantly, the ability for partial matching. Experiment results show that it is about 15 times faster than OCR. It is a promising technique to boost better document image retrieval.
基于字形编码的文档图像关键词识别
有了庞大的文档图像数据库,用户在文档中查找关键字的方法就很有用了。一种方法是对每个文档执行光学字符识别(OCR),然后对结果文本进行索引。但是,如果文档质量差或时间紧迫,则不可能对所有图像进行完整的OCR。本文建立在先前关于词形编码的工作基础上,提出了一种替代技术和特征描述符的组合,用于不使用OCR的关键字识别。不同的序列比对相似性度量可用于部分或整个单词匹配。所提出的技术可以容忍衬线、字体样式和一定程度的触摸、破碎或重叠字符。与以往的算法相比,该算法不仅具有更高的精度和更低的碰撞率,更重要的是具有部分匹配的能力。实验结果表明,该算法比OCR算法快15倍左右。它是一种很有前途的技术,可以提高文档图像检索的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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