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Arabic (Indian) handwritten digits recognition using Gabor-based features

机译:阿拉伯语(印度人)手写数字使用基于Gabor的特征识别

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Arabic (Indian) handwritten digits recognition is useful in a large variety of banking and business applications and in postal zip code reading, and data entry applications. In this paper we present a technique for the automatic recognition of Arabic (Indian) handwritten digits using Gabor-based features and Support Vector Machines (SVMs). A database consisting of 21120 samples written by 44 writers is used. 70% of the data is used for training and the remaining 30% is used for testing. Several scales and orientations are used to extract the Gaborbased features. The achieved average recognition rates are 99.85% and 97.94% using 3 scales & 5 orientations and using 4 scales & 6 orientations, respectively. The experimental results indicate the effectiveness of the Gabor-based features and SVM for Arabic (Indian) digits recognition.
机译:阿拉伯语(印度人)手写的数字识别对于各种银行和业务应用以及邮政邮政编码和数据输入应用程序有用。在本文中,我们介绍了一种使用Gabor的特征和支持向量机(SVM)自动识别阿拉伯语(印度)手写数字的技术。使用由44个作家写入的21120个样本组成的数据库。 70%的数据用于培训,其余30%用于测试。使用几种尺度和方向来提取具有伸出的特征。使用3刻度和5个方向和使用4尺度和6方向,实现平均识别率为99.85%和97.94%。实验结果表明,阿拉伯语(印度)数字识别的基于Gabor的特征和SVM的有效性。

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