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Investigating of Preprocessing Techniques and Novel Features in Recognition of Handwritten Arabic Characters

机译：手写阿拉伯字符识别中的预处理技术和新功能的研究

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摘要

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.
机译：手写阿拉伯文识别系统面临许多困难，例如字符形状的无限变化。本文介绍了一种手写阿拉伯字符识别的新方法。我们提出了一种新颖的有效方法来识别离线阿拉伯手写字符。该方法基于新颖的预处理操作，角色主体以及辅助组件的结构统计和拓扑特征。对所选功能的重要性和准确性进行了评估。我们基于所选功能和系统的方法是由CENPRMI数据集构建，训练和测试的。我们使用SVM（RBF）和KNN进行分类，以找到识别精度。所提算法在准确性方面取得了可喜的成果。支持向量机的识别率为89.2％。与其他相关作品以及我们最近发表的作品相比，我们发现我们的结果是其中最高的。

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