Performance evaluation of a mathematical formula recognition system with a large scale of printed formula images

This paper shows the performance evaluation of the mathematical formula recognition system applied to a large scale of printed formula images, which has been developed in our laboratory. Our laboratory has collaborated with Michler of University of Essen, Germany, on project of "Retro-digitalization of mathematical journals, and their integration searchable digital libraries". In this project, two kinds of mathematical journals were scanned for digitalization. In this process, we cut out formulas manually from many pages, and created the answer database, "Ground-Truth." We report the results of performance evaluation with respect to the recognition of symbols, various types of sub-expressions and whole expressions of mathematical formulas.