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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Investigating of Preprocessing Techniques and Novel Features in Recognition of Handwritten Arabic Characters
verfasst von : Ahmed. T. Sahlol, Ching Y. Suen, Mohammed R. Elbasyoni, Abdelhay A. Sallam
Erschienen in: Artificial Neural Networks in Pattern Recognition
Verlag: Springer International Publishing
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There are many difficulties facing a handwritten Arabic recognition system such as unlimited variation in character shapes. This paper describes a new method for handwritten Arabic character recognition. We propose a novel efficient approach for the recognition of off-line Arabic handwritten characters. The approach is based on novel preprocessing operations, structural statistical and topological features from the main body of the character and also from the secondary components. Evaluation of the importance and accuracy of the selected features was made. Our method based on the selected features and the system was built, trained and tested by CENPRMI dataset. We used SVM (RBF) and KNN for classification to find the recognition accuracy. The proposed algorithm obtained promising results in terms of accuracy; with recognition rates of 89.2% for SVM. Compared with other related works and also our recently published work we find that our result is the highest among them.