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FPGA-Based Farsi Handwritten Digit Recognition System

A new method for feature extraction based on FPGA (Field Programmable Gate Arrays) implementation is proposed in this paper. The specific application is offline Farsi handwritten digit recognition. The classification is based on a simple two layer MLP (Multi Layer Perceptron). This method of feature extraction is appropriate for FPGA implementation as it can be implemented only with addition and subtraction operations. The proposed method is used to extract the features from normalized 40×40 pixel handwritten digit images from Standard Hoda database. Exprimentally results showed that the proposed system achived about 96% accuracy. Overally the system is simple, more accurate and less complex than the other similar systems.