Handwritten Character Recognition Using Gray-scale Based State-Space Parameters and Class Modular NN
V. L. Lajish · 2008
We present a novel feature extraction method for offline recognition of segmented Malayalam handwritten characters from their gray-scale images without the usual step of binarization. We investigate a new approach to model handwritten characters using State-Space Map (SSM) and State-Space Point Distribution (SSPD) parameters. In the recognition stage we used class modular neural network with the propsed SSPD features and this method is found to be promising.