Offline Urdu Nastaleeq Optical Character Recognition Based on Stacked Denoising Autoencoder

Offline Urdu Nastaleeq text recognition has long been a serious problem due to its very cursive nature. In order to get rid of the character segmentation problems, many researchers are shifting focus towards segmentation free ligature based recognition approaches. Majority of the prevalent ligature...

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Bibliographic Details
Published in:	China communications Vol. 14; no. 1; pp. 146 - 157
Main Authors:	Ahmad, Ibrar, Wang, Xiaojie, Li, Ruifan, Rasheed, Shahid
Format:	Journal Article
Language:	English
Published:	China Institute of Communications 2017 Center for Intelligence of Science and Technology(CIST), School of Computer Science,Beijing University of Posts and Telecommunications, No.10 Xitucheng Road, Beijing 100876, China%Pakistan Telecommunication Company Limited(PTCL), Islamabad 44000, Pakistan
Subjects:	Character recognition classification deep learning denoising autoencoder Feature extraction Hidden Markov models Noise reduction offline printed ligature recognition Optical character recognition software Training urdu nastaleeq Writing urdu nastaleeq deep learning offline printed ligature recognition denoising autoencoder classification
ISSN:	1673-5447
Online Access:	Get full text
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