  One of the most arduous and captivating domains under image processing is
handwritten character recognition. In this paper we have proposed a feature
extraction technique which is a combination of unique features of geometric,
zone-based hybrid, gradient features extraction approaches and three different
neural networks namely the Multilayer Perceptron network using Backpropagation
algorithm (MLP BP), the Multilayer Perceptron network using Levenberg-Marquardt
algorithm (MLP LM) and the Convolutional neural network (CNN) which have been
implemented along with the Minimum Distance Classifier (MDC). The procedures
lead to the conclusion that the proposed feature extraction algorithm is more
accurate than its individual counterparts and also that Convolutional Neural
Network is the most efficient neural network of the three in consideration.

Computer Vision and Pattern Recognition