Paper Title
Handwritten Digit Recognition Using Back Propagation Neural Network& K-Nearest Neighbour Classifier

Handwriting recognition has become one of the hottest directions in the field of image processing. It can very well transform any handwritten content into a plain text file. This is being widely used in cheque recognition, mail sorting, scanning documents, reading aid for the blind and so on. This paper attempts to recognize handwritten digits using Backpropagation (BP) neural network and k-Nearest Neighbour Algorithm and then compare the results to suggest an optimum classifier amongst the two of them.