Bit Pattern based Sindhi Character Recognition using Neural Network

In this paper, bit pattern based character recognition for Sindhi language has been presented. The characters of sindhi language are very much complexed to recognize for particular domain. Although there are many studies that have already been done in this recognition but all those are based on image recognition, to give novelty in the idea our system uses bit patterns for characters and provide outcome on the basis of that input pattern. A data set with nine no. of inputs and six outputs for each character is created. We have used patterns due to the computational complexity constant that are 3X3 matrix for input patterns that are uniquely created for all characters and output will be generated in form of binary pattern for the particular character sequence numbers. This system reads the 3X3 matrix in clock wise pattern to get input pattern and match it to created data set. To train the data we have used a Neural Network Model, Multi-Layer Perceptron (MLP) with significant number of hidden layers to get measurable results. The accuracy of 82.6% has been achieved by the experiment.