Font adaptation of an HMM-based OCR system

Kamel Ait-Mohand; Laurent Heutte; Thierry Paquet; Nicolas Ragot

doi:10.1117/12.840321

18 January 2010 Font adaptation of an HMM-based OCR system

Kamel Ait-Mohand, Laurent Heutte, Thierry Paquet, Nicolas Ragot

Proceedings Volume 7534, Document Recognition and Retrieval XVII; 75340J (2010) https://doi.org/10.1117/12.840321
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

Abstract

We create a polyfont OCR recognizer using HMM (Hidden Markov models) models of character trained on a dataset of various fonts. We compare this system to monofont recognizers showing its decrease of performance when it is used to recognize unseen fonts. In order to fill this gap of performance, we adapt the parameters of the models of the polyfont recognizer to a new dataset of unseen fonts using four different adaptation algorithms. The results of our experiments show that the adapted system is far more accurate than the initial system although it does not reach the accuracy of a monofont recognizer.

Citation Download Citation

Kamel Ait-Mohand, Laurent Heutte, Thierry Paquet, and Nicolas Ragot "Font adaptation of an HMM-based OCR system", Proc. SPIE 7534, Document Recognition and Retrieval XVII, 75340J (18 January 2010); https://doi.org/10.1117/12.840321

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