- Dmitriy Genzel
- Ashok C. Popat
- Nemanja Spasojevic
- Michael Jahr
- Andrew Senior
- Eugene Ie
- Frank Yung-Fong Tang
ICDAR-2011
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.
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