期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：10
出版社：Journal of Theoretical and Applied
摘要：The Arabic Language had a little attention in this field compared with other languages due to the high cursive nature of the handwritten Arabic language, especially with their dots. The difficulty lies in the complexity of locating the wavy shape in the characters, which solved by the combination of certain features extraction methods that work in separate way. The proposed of Isolated Arabic off-line handwritten recognition system based on two stages classifiers (Hybrid). First stage is a linear Support Vector Machine (SVM) for splitting the dataset characters into two groups - Characters with dots and Characters without dots, by giving certain extraction features to each group. This division can reduce the error rate of characters recognition which has similar looking shape. Second stage supplies the first stage result to Neural Network (NN) stage which granted one of the best correctness and accuracy by training. Finally, a fully recognized character is acquired successfully. This work is implemented (IFN/ENIT) dataset, the system significantly reduce the load of NN process by SVM classifier, which can be used for real-time applications. A total accuracy of this proposed work reaches 92.2%
关键词：Arabic Handwritten; Optical Character Recognition. Support Vector Machine; Feature Extraction; Neural Network; IFN/ENIT. ;
