Translation-Inspired OCR

Dmitriy Genzel
Nemanja Spasojevic
Michael Jahr
Frank Yung-Fong Tang
ICDAR-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.

Research Areas