On Bangla character recognition
Sanjit Kumar Saha, Md. Shamsuzzaman, Md. Al-Amin Bhuiyan · 2010
A recent surge of interest is to recognize Bangla characters. Bangla characters represent complex, multidimensional and meaningful visual information and developing a computational model for Bangla character recognition is a challenging job. This research presents a hybrid neural network solution for Bangla character recognition which combines local image sampling and artificial neural network. The method is based on BAM for dimensional reduction and multi-layer perception with backpropagation algorithm has been used for training the network. It has been found from practical observations that the number of iterations required to train the network is enormous. The capability of recognition of a neural network increases with increasing the training accuracy. For this process each character is converted to a designated M×N feature matrix. These feature matrices of characters are then fed into the neural network as input patterns .The neural network is trained with the set of input patterns of the digits to acquire separate knowledge corresponding to each Bangla character. In order to justify the effectiveness of the system, different test patterns of the characters are used to verify the system. Experimental results demonstrate that the system is capable of recognizing Bangla characters with 98% accuracy.