Arabic Character Recognition Using a Combination of k-means and k-NN Algorithms

In this paper, a novel approach to Arabic character recognition is proposed. The system is based upon the k-means algorithm and the k-nearest neighbors (k-NN) algorithm that employs the Mahalanobis distance measure. In the proposed system, each input character is mapped to its class using a minimum distance classifier. To demonstrate the merits of the proposed system, its performance is compared to that of a standard Support Vector Machine (SVM) solution. Simulation results have revealed that the proposed system has a lower time complexity and always produces lower error rates (higher success rates) than the current SVM solutions

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