An Arabic Optical Character Recognition System Using Restricted Boltzmann Machines View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2013

AUTHORS

Abdullah M. Rashwan , Mohamed S. Kamel , Fakhri Karray

ABSTRACT

Most of the state-of-the-art Arabic Optical Character Recognition systems use Hidden Markov Models to model Arabic characters. Much of the attention is paid to provide the HMM system with new features, pre-processing, or post-processing modules to improve the performances. In this paper, we present an Arabic OCR system using Restricted Boltzmann Machines (RBMs) to model Arabic characters. The recently announced ALTEC dataset for typewritten OCR system is used to train and test the system. The results show a 26% increase in the average word accuracy rate and 8% increase in the average character accuracy rate compared to the HMM system. More... »

PAGES

108-115

Book

TITLE

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

ISBN

978-3-642-41826-6
978-3-642-41827-3

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-41827-3_14

DOI

http://dx.doi.org/10.1007/978-3-642-41827-3_14

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1013019790


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