Hand written digit recognition system for South Indian languages using artificial neural networks

In this paper a novel approach for recognition of handwritten digits for South Indian languages using artificial neural networks (ANN) and Histogram of Oriented Gradients (HOG) features is presented. The images of documents containing the hand written digits are optically scanned and are segmented into individual images of isolated digits. HOG features are then extracted from these images and applied to the ANN for recognition. The system recognises the digits with an overall accuracy of 83.4%.