Applying the T-Recs table recognition system to the business letter domain

T. Kieninger, A. Dengel
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引用次数: 80

Abstract

This paper summarizes the core idea of the T-Recs table recognition system, an integrated system covering block-segmentation, table location and a model-free structural analysis of tables. T-Recs works on the output of commercial OCR systems that provide the word bounding box geometry together with the text itself (e.g. Xerox ScanWorX). While T-Recs performs well on a number of document categories, business letters still remained a challenging domain because the T-Recs location heuristics are mislead by their header or footer resulting in a low recognition precision. Business letters such as invoices are a very interesting domain for industrial applications due to the large amount of documents to be analyzed and the importance of the data carried within their tables. Hence, we developed a more restrictive approach which is implemented in the T-Recs++ prototype. This paper describes the ideas of the T-Recs++ location and also proposes a quality evaluation measure that reflects the bottom-up strategy of either T-Recs or T-Recs++. Finally, some results comparing both systems on a collection of business letters are given.
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T-Recs表识别系统在商务信函领域的应用
本文总结了T-Recs表识别系统的核心思想,这是一个集块分割、表定位和表无模型结构分析为一体的系统。T-Recs用于商业OCR系统的输出,这些系统提供单词边界框几何形状以及文本本身(例如Xerox ScanWorX)。虽然T-Recs在许多文档类别上表现良好,但商业信件仍然是一个具有挑战性的领域,因为T-Recs的位置启发式受到标题或页脚的误导,导致识别精度较低。由于需要分析大量的文档以及表格中所包含的数据的重要性,诸如发票之类的商业信件对于工业应用来说是一个非常有趣的领域。因此,我们开发了一种更严格的方法,并在t - recs++原型中实现。本文阐述了T-Recs++的定位思路,并提出了一种反映T-Recs或T-Recs++自下而上策略的质量评价指标。最后,给出了两种系统在商业信函集上的比较结果。
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