NDLI: Handwritten Farsi/Arabic Word Recognition

Content Provider	IEEE Xplore Digital Library
Author	Broumandnia, A. Shanbehzadeh, J. Nourani, M.
Copyright Year	2007
Description	Author affiliation: lslamic Azad Univ.-Tehran South Branch, Tehran (Broumandnia, A.)
Abstract	This paper presents a novel holistic handwritten Farsi /Arabic word recognition scheme in situation where we face with word rotation and scale change. Image words features are extracted by exploiting rotation and scale invariance characteristics of M-Band packet wavelet transform performed on polar transform version of images of handwritten Farsi/Arabic words. The extracted features construct a feature vector for each word image. This vector is employed in recognition phase by finding the similar words based on the least Mahalanobis distance of feature vectors. This scheme is robust against rotation and scaling. Experimental results, obtained from testing different handwritten texts with various orientations and scales, show that proposed scheme outperforms Fourier-wavelet and Zernike moments algorithms. The robustness of new scheme has been tested with images corrupted by Gaussian noise and compared with similar schemes. Experimental results show that the accuracy of our algorithm reaches 95.8 percents.
Starting Page	767
Ending Page	771
File Size	5532468
Page Count	5
File Format	PDF
ISBN	1424410304
DOI	10.1109/AICCSA.2007.370719
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-05-13
Publisher Place	Jordan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Handwriting recognition Wavelet transforms Wavelet packets Feature extraction Text recognition Discrete wavelet transforms Character recognition Shape Wavelet coefficients Face recognition Wavelet Transform Pattern Recognition Farsi/Arabic Handwritings Recognition
Content Type	Text
Resource Type	Article

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