Abstract
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 21720 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 Gabor-based 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.