Abstract

The BBN Byblos OCR system implements a script-independent methodology for OCR using hidden Markov models (HMMs). We have successfully ported the system to Arabic, Pashto, English, and Chinese. We discuss our effort in configuring the system to perform recognition of noisy machine printed Japanese documents. The data for our experimentation was taken from the University of Washington (UW-II) Japanese OCR corpus and the LDC Japanese Business News Supplement corpus. We evaluated the performance of a whole-character configuration in which each character was modeled using a separate HMM. As in the case of our Chinese OCR system [P. Natarajan et al., 2001], we also used a sub-character modeling approach [P. Natarajan et al., 2003] in which each Japanese character was spelled using a shared set of automatically generated sub-characters. We experimentally evaluated the …

Date

2004

Authors

Ehry MacRostie, Premkumar Natarajan, Michael Decerbo, Rohit Prasad

Conference

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.

Volume

2

Pages

650-653

Publisher

IEEE