Mathematical Formula Identification in PDF Documents

Xiaoyan Lin, Liangcai Gao, Zhi Tang, Xiaofan Lin, Xuan Hu

Abstract: Recognizing mathematical expressions in PDF documents is a new and important field in document analysis. It is quite different from extracting mathematical expressions in image-based documents. In this paper, we propose a novel method by combining rule-based and learning-based methods to detect both isolated and embedded mathematical expressions in PDF documents. Moreover, various features of formulas, including geometric layout, character and context content, are used to adapt to a wide range of formula types. Experimental results show satisfactory performance of the proposed method. Furthermore, the method has been successfully incorporated into a commercial software package for large-scale Chinese e-Book production.