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Journal of Electronic Imaging • new

Character context: a shape descriptor for Arabic handwriting recognition
Author(s): Mohammed Mudhsh; Rolla Almodfer; Pengfei Duan; Shengwu Xiong
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Paper Abstract

In the handwriting recognition field, designing good descriptors are substantial to obtain rich information of the data. However, the handwriting recognition research of a good descriptor is still an open issue due to unlimited variation in human handwriting. We introduce a “character context descriptor” that efficiently dealt with the structural characteristics of Arabic handwritten characters. First, the character image is smoothed and normalized, then the character context descriptor of 32 feature bins is built based on the proposed “distance function.” Finally, a multilayer perceptron with regularization is used as a classifier. On experimentation with a handwritten Arabic characters database, the proposed method achieved a state-of-the-art performance with recognition rate equal to 98.93% and 99.06% for the 66 and 24 classes, respectively.

Paper Details

Date Published: 6 November 2017
PDF: 10 pages
J. Electron. Imag. 26(6) 063002 doi: 10.1117/1.JEI.26.6.063002
Published in: Journal of Electronic Imaging Volume 26, Issue 6
Show Author Affiliations
Mohammed Mudhsh, Wuhan Univ. of Technology (China)
Rolla Almodfer, Wuhan Univ. of Technology (China)
Pengfei Duan, Wuhan Univ. of Technology (China)
Hubei Key Lab. of Transportation Internet of Things (China)
Shengwu Xiong, Wuhan Univ. of Technology (China)
Hubei Key Lab. of Transportation Internet of Things (China)

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