A Front-End OCR for Omni-Font Persian/Arabic Cursive Printed Documents

Authors:
Ramin Mehran;Hamed Pirsiavash;Farbod Razzazi
Affiliations:
K.N.Toosi University of Technology and Paya Soft Co.;Sharif University of Technology and Paya Soft Co.;Paya Soft Co.
Venue:
DICTA '05 Proceedings of the Digital Image Computing on Techniques and Applications
Year:
2005

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Pattern Recognition Letters

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Abstract

Compared to non-cursive scripts, optical character recognition of cursive documents comprises extra challenges in layout analysis as well as recognition of the printed scripts. This paper presents a front-end OCR for Persian/Arabic cursive documents, which utilizes an adaptive layout analysis system in addition to a combined MLP-SVM recognition process. The implementation results on a comprehensive database show a high degree of accuracy which meets the requirements of commercial use.