PASHTO OPTICAL CHARACTER RECOGNITION USING NEURAL NETWORK
This paper presents an Optical Character Recognition system for printed/scanned Pashto continuous text. In the proposed work, Pashto text is recognized using Feed Forward Neural Network (FFNN), consist of an input layer, a hidden layer and an output layer. The input layer is composed of 315 neurons, which receive the pixels data i.e. binary data from a 21x15 symbol pixel matrix. The hidden layer contains 2000 neurons which has been chosen after testing based on optimal result, while the output layer is composed of 6 neurons. As the joinable Pashto characters on different locations in text change its size and shapes, as a result 60 Pashto characters with 110 samples for each Pashto character has been used to train the network.
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