This paper describes a NEURAL NETWORK based technique for feature extraction applicable to segmentation-based word recognition systems. The proposed system extracts the geometric features of the character contour.. The system gives a feature vector as its output. The feature vectors so generated from a training set, were then used to train a pattern recognition engine based on Neural Networks so that the system can be benchmarked. Since, an attempt was made to develop a system that used the methods that humans use to perceive handwritten characters. Hence a system that recognizes handwritten characters using Pattern recognition was developed.Here the data generated by comparison of two images was stored in excel format and then calling that data as an indivual input for generation of simulink diagram. Pattern recognition can be used to model human perception. The mathematics that Pattern recognition requires is extremely fundamental. Thus, any algorithm developed using Pattern recognition would require relatively simple and short calculations. Due to simplicity of calculations, they can be implemented on any hardware or software platform without too much concern for computing power. In this paper first part is about introduction to character Recognition. Then next part giving short introduction to Neuarl network implementaion for image processing using MATLAB.

Author Name: Prof..Sachin Patel

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Keywords: Pattern recognition, image processing, handwritten character recognition, Euclidean distance, nearest neighbour algorithm, database, HCR, MATLAB Commands:bwmorph,imdilate,reshape,strlen,xor.

ISSN: 2320-5547

EISSN: 2320-5547

EOI/DOI:

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