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An Hybrid Approach for Recognition of Handwriten Devnagri compound characters


An Hybrid Approach for Recogni

Clustering and Retrieval of Vi

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Abstract


Handwriting has always been a primary tool of communication. New technologies have been developed in order to record this handwritten information. Special techniques describe nature of handwritten scripts and have proposed methods to convert it into electronic data. We already have a method of feature extraction for identification of single unit Devnagri character in the form of images known as OCR. In our proposed system, we have imposed some algorithms to identify human written Devanagri scripts that make it flexible, without for feature extraction in character recognition technique are compared to get the best result. This overcomes a variety of limitations of OCR technique. The different algorithms used are Genetic, Neural Network and Thinning algorithm. The comparison of results obtained by these algorithms is made here. This work is focused on improvising the character recognition capability of feed-forward back-propagation neural network by using one, two and three hidden layers. The recognition accuracy was improved further when modified additional momentum term was used

KeyWords
OCR,CharacterRecognition,GeneticAlgorithm,NeuralNetwork,Thinning,Back-propagation,MomentumTerm



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