Karim Abdul Hassan, A., Alawi, M. (2017). Proposed Handwriting Arabic Words classification Based On Discrete Wavelet Transform and Support Vector Machine. Alustath, 58(2), 1159-1168.
Alia Karim Abdul Hassan; Mohammed Alawi. "Proposed Handwriting Arabic Words classification Based On Discrete Wavelet Transform and Support Vector Machine". Alustath, 58, 2, 2017, 1159-1168.
Karim Abdul Hassan, A., Alawi, M. (2017). 'Proposed Handwriting Arabic Words classification Based On Discrete Wavelet Transform and Support Vector Machine', Alustath, 58(2), pp. 1159-1168.
Karim Abdul Hassan, A., Alawi, M. Proposed Handwriting Arabic Words classification Based On Discrete Wavelet Transform and Support Vector Machine. Alustath, 2017; 58(2): 1159-1168.

Proposed Handwriting Arabic Words classification Based On Discrete Wavelet Transform and Support Vector Machine

Iraqi Journal of Science
Article 1, Volume 58, Issue 2, March 2018, Pages 1159-1168
Authors
Alia Karim Abdul Hassan; Mohammed Alawi
Abstract
A proposed feature extraction algorithm for handwriting Arabic words. The proposed method uses a 4 levels discrete wavelet transform (DWT) on binary image. sliding window on wavelet space and computes the stander derivation for each window. The extracted features were classified with multiple Support Vector Machine (SVM) classifiers. The proposed method simulated with a proposed data set from different writers. The experimental results of the simulation show 94.44% recognition rate.
Keywords
Handwriting Word Recognition; Binarization; Feature Selection DWT; SVM
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