Error detection, error correction and performance evaluation in on-line mathematical expression recognition

Automatic recognition of on-line mathematical expressions is di$cult especially when there exist errors. In this paper, we incorporate an error detection and correction mechanism into a parser developed previously by us based on de"nite clause grammar (DCG). The resulting system can handle lexical, syntactic and some semantic errors. The recognition speed for 600 commonly seen expressions is quite acceptable, ranging from 0.73 to 6 s per expression on a modest workstation. In addition, we propose a performance evaluation scheme which can be used to demonstrate the e!ectiveness of both the symbol recognition and structural analysis stages by a single measure. 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

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