Development of OCR (optical character recognition) system for scientific documents

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In this research, we developed an OCR system adapted to scientific documents, in view of its application to retro-digitization of mathematical journals and automatic Braille transcription of mathematical documents. The target images are those obtained from clearly printed documents by 400-600DPI scanner.Since there is no commercial OCR software which can recognize mathematical symbols, we developed our own OCR engine. It recognizes with about 450 kinds of characters and symbols used in mathematical expressions, and distinguishes well the italic fonts and upright fonts of alphabets.For the recognition of text areas, there are several efficient post-processing methods to improve recognition results using linguistic information, while in mathematical expression areas, some other different methods of post-processing based on the structure of mathematical notations are efficient. Therefore, we developed algorithms to separate text area and mathematical expression areas, for both Japanese and English documents.As for the structure analysis of mathematical expressions, we developed a new method, robust against the recognition errors of characters and similar characters of different sizes. We first construct a network joining characters (symbols) by possible links of relations with cost, Finally, we obtain the result of the recognition of mathematical formulas as the spanning tree of minimum cost of the network, after reevaluating the candidates by using the cost reflecting global structure of the mathematical expressions. The advantage of this method is that local errors of the recognition are recovered automatically by the total cost of the recognition tree.We also developed handwriting interface to edit mathematical expressions to use it as an easy user interface to correct the recognition errors of mathematical expressions.