Retrieval methods for English-text with misrecognized OCR characters

M. Ohta, A. Takasu, J. Adachi

Research output: Contribution to conferencePaper

25 Citations (Scopus)

Abstract

This paper presents three probabilistic text retrieval methods designed to carry out a full-text search of English documents containing OCR errors. By searching for any query term on the premise that there are errors in the recognized text, the methods presented can tolerate such errors, and therefore costly manual post-editing is not required after OCR recognition. In the applied approach, confusion matrices are used to store characters which are likely to be interchanged when a particular character is missrecognized, and the respective probability of each occurrence. Moreover, a 2-gram matrix is used to store probabilities of character connection, i.e., which letter is likely to come after another. Multiple search terms are generated for an input query term by making reference to confusion matrices, after which a full-text search is run for each search term. The validity of retrieved terms is determined based on error-occurrence and character-connection probabilities. The performance of these methods is experimentally evaluated by determining retrieval effectiveness, i.e., by calculating recall and precision rates. Results indicate marked improvement in comparison with exact matching.

Original languageEnglish
Pages950-956
Number of pages7
Publication statusPublished - Jan 1 1997
Externally publishedYes
EventProceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2) - Ulm, Ger
Duration: Aug 18 1997Aug 20 1997

Other

OtherProceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2)
CityUlm, Ger
Period8/18/978/20/97

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Ohta, M., Takasu, A., & Adachi, J. (1997). Retrieval methods for English-text with misrecognized OCR characters. 950-956. Paper presented at Proceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2), Ulm, Ger, .