A bottom-up OCR system for mathematical formulas recognition

Authors:
Wei Wu;Feng Li;Jun Kong;Lichang Hou;Bingdui Zhu
Affiliations:
Dept. Appl. Math., Dalian University of Technology, Dalian, China;Dept. Appl. Math., Dalian University of Technology, Dalian, China;Northeast Normal University, Changchun, China;Dept. Appl. Math., Dalian University of Technology, Dalian, China;Dept. Appl. Math., Dalian University of Technology, Dalian, China
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Year:
2006

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Abstract

An OCR system is presented to understand mathematical formulas in binary printed document images. The system utilizes a novel component-labeling algorithm for extracting local maximum components from image, and uses these components to locate the mathematical formulas. A character recognition algorithm based on neural networks is then adopted. For segmenting merged characters in the image, a novel segmentation algorithm based on a modified SOM neural network was introduced into the system. With the employment of LL(1) grammar, this system can convert the recognition results into a $\mbox{\LaTeX}$ file.