A robust free size OCR for omni-font persian/arabic printed document using combined MLP/SVM

Authors:
Hamed Pirsiavash;Ramin Mehran;Farbod Razzazi
Affiliations:
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran;Department of Electrical Engineering, K.N.Toosi Univ. of Tech., Tehran, Iran;Paya Soft co., Tehran, Iran
Venue:
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
Year:
2005

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Abstract

Optical character recognition of cursive scripts present a number of challenging problems in both segmentation and recognition processes and this attracts many researches in the field of machine learning. This paper presents a novel approach based on a combination of MLP and SVM to design a trainable OCR for Persian/Arabic cursive documents. The implementation results on a comprehensive database show a high degree of accuracy which meets the requirements of commercial use.