A Hybrid Recognition Scheme Based on Partially Labeled SOM and MLP
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Abstract
We propose a hybrid system for Bangla handwritten numeral recognition based on partially labeled two-layer SOM and MLP classifiers. Partially labeled mechanism is introduced to the Kohonen’s SOM for reducing recognition error rate, and two-layer structure is applied for improving the performance of the SOM classifier. The directional and density features are utilized in our system, and the partially labeled SOM is applied first. In the case that the character cannot be recognized by the partially labeled SOM, it will be feed to a multi-layer perceptron classifier for further processing. The experiments on the Bangla handwritten numeral samples captured from real envelopes have found that the hybrid system achieves 96.7% correct recognition rate.
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