基于符号优势的PDF文档公式识别方法

2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR) Pub Date : 2017-11-01 DOI:10.1109/ICDAR.2017.189

Xiaode Zhang, Liangcai Gao, Ke Yuan, Runtao Liu, Zhuoren Jiang, Zhi Tang

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引用次数: 9

摘要

随着越来越多的科学文献以PDF格式出现，对PDF格式文献中的公式进行识别具有重要意义。本文提出了一种基于符号优势的公式识别方法，利用直接从PDF文件中提取的丰富信息来恢复公式结构。公式的层次结构用关系树表示，并基于符号优势递归构建关系树，既考虑了符号的空间布局，又考虑了数学的排版习惯。此外，我们还提出了一种特殊的字符识别方法来识别具有多个组件或可变unicode的公式字符。在IM2LATEX-100K和PDFME-10K两个大型数据集上进行了可重复和可比较的实验。实验结果表明，与现有的两种公式识别系统(INFTY和WYGIWYS)相比，该方法对PDF文档具有更强的适应性和实用性。

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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A Symbol Dominance Based Formulae Recognition Approach for PDF Documents

With more and more scientific documents becoming available in PDF format, recognition of formulae in these PDF documents is of great significance. In this paper, we propose a symbol dominance based formulae recognition approach to recovering formulae structures by using the rich information extracted directly from PDF files. The hierarchical structure of formula is represented by relationship tree, and the tree is built recursively based on symbol dominance, which considers both the spatial layout of symbols and the typesetting conventions of mathematics. In addition, we propose a special character recognition method to identify the formula characters with multiple components or variable unicode. Repeatable and comparable experiments have been done over two large datasets, IM2LATEX-100K and PDFME-10K. Experimental results demonstrate that our method is more adaptive and practical for PDF documents compared with other two existing available formulae recognition systems, INFTY and WYGIWYS.

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2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)

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