Handwritten Malayalam Word Recognition System using Neural Networks
International Journal of Engineering Research and
The work describe an intelligent system for free hand entry of characters and words using light pen model. The system developed will recognize the character and words. The various approaches for handwritten character recognition are studied in the literature review phase. The different approaches are string matching schemes, structural approach, Template matching, using neural networks etc. The central objective of this project is demonstrating the capabilities of Artificial Neural Network
... Neural Network implementations with back propagation algorithm in recognizing Malayalam characters. An emerging technique in the character recognition application area is the use of Artificial Neural Network implementation with networks employing specific guides (learning rules ) to update the links (weights )between their nodes .Such network can be fed the data from the graphic analysis of the input picture and trained to output characters on one or another form . One such network with supervised learning rule is the Multi -Layer Perception (MLP) model. It uses the generalized Delta Learning Rule for adjusting its weight and can be trained for a set of input /desire output values in a number of iterations. The very nature of this particular model is that it will force the output to one of nearby values if a variation of input is fed to the network that it is not the technical approach is followed is processing input characters detecting line segments, obtaining the direction feature vector and training the network for a set of desired characters corresponding to the input characters. Finally, the word is recognized by checking the database trained for, thus solving the proximity issue.