A Robust Free Size OCR for Omni-Font Persian/Arabic Printed Document Using Combined MLP/SVM
Identifieur interne : 001387 ( Main/Merge ); précédent : 001386; suivant : 001388A Robust Free Size OCR for Omni-Font Persian/Arabic Printed Document Using Combined MLP/SVM
Auteurs : Hamed Pirsiavash [Iran, États-Unis] ; Ramin Mehran [Iran] ; Farbod Razzazi [Iran]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2005.
Abstract
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.
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DOI: 10.1007/11578079_63
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