Approximate string matching algorithms for limited-vocabulary OCR output correction

Thomas A. Lasko; Susan E. Hauser

doi:10.1117/12.410841

21 December 2000 Approximate string matching algorithms for limited-vocabulary OCR output correction

Thomas A. Lasko, Susan E. Hauser

Proceedings Volume 4307, Document Recognition and Retrieval VIII; (2000) https://doi.org/10.1117/12.410841
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

Five methods for matching words mistranslated by optical character recognition to their most likely match in a reference dictionary were tested on data from the archives of the National Library of Medicine. The methods, including an adaptation of the cross correlation algorithm, the generic edit distance algorithm, the edit distance algorithm with a probabilistic substitution matrix, Bayesian analysis, and Bayesian analysis on an actively thinned reference dictionary were implemented and their accuracy rates compared. Of the five, the Bayesian algorithm produced the most correct matches (87%), and had the advantage of producing scores that have a useful and practical interpretation.

Citation Download Citation

Thomas A. Lasko and Susan E. Hauser "Approximate string matching algorithms for limited-vocabulary OCR output correction", Proc. SPIE 4307, Document Recognition and Retrieval VIII, (21 December 2000); https://doi.org/10.1117/12.410841

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