Translation-Inspired OCR

Authors:
Dmitriy Genzel;Ashok C. Popat;Nemanja Spasojevic;Michael Jahr;Andrew Senior;Eugene Ie;Frank Yung-Fong Tang
Affiliations:
-;-;-;-;-;-;-
Venue:
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
Year:
2011

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Abstract

Optical character recognition is carried out using techniques borrowed from statistical machine translation. In particular, the use of multiple simple feature functions in linear combination, along with minimum-error-rate training, integrated decoding, and $N$-gram language modeling is found to be remarkably effective, across several scripts and languages. Results are presented using both synthetic and real data in five languages.