Handwriting Word Recognition Based on SVM Classifier
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2015, Vol 6, Issue 11
Abstract
This paper proposed a new architecture for handwriting word recognition system Based on Support Vector Machine SVM Classifier. The proposed work depends on the handwriting word level, and it does not need for character segmentation stage. An Arabic handwriting dataset AHDB, dataset used for train and test the proposed system. Besides, the system achieved the best recognition accuracy 96.317% based on several feature extraction methods and SVM classifier. Experimental results show that the polynomial kernel of SVM is convergent and more accurate for recognition than other SVM kernels.
Authors and Affiliations
Mustafa Kadhm, Asst. Prof. Dr. Alia Hassan
Keywords
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- EP ID EP159092
- DOI 10.14569/IJACSA.2015.061109
- Views 105
- Downloads 0
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