Arabic Character Recognition Using Gabor Filters

A technique for the Automatic recognition of Arabic characters using Gabor filters is presented. K-Nearest Neighbor (KNN) is used for classification. Although KNN is a simple classifier, the achieved recognition rates proved that Gabor filters are effective in the classification of Arabic characters. Different number of orientations and scales, resulting in 30 and 48 feature vector sizes, are used and the recognition rates compared. A high recognition rate of 99.57%.is achieved using 30 features (3 scales and 5 orientations). The results are compared with two previously published techniques using Modified Fourier Spectrum and Fourier descriptors using the same data. This technique has 2.6% and 4% higher recognitions rate than Fourier descriptors and Modified Fourier Spectrum descriptors, respectively

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