Nearest Neighbor Algorithm in Handwritten Character.

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 is then used to train a pattern recognition engine based on Neural Networks so that the system can be benchmarked. There was an attempt 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 comparing two images was stored in excel format and then that data was called as an individual input for generation of Simulink diagram. Pattern recognition can be used to model human perception. The mathematics that Pattern recognition requires is extremely fundamental. Any algorithm developed using Pattern recognition would require relatively simple and not so lengthy calculations. Due to simplicity of calculations, they can be implemented on any hardware or software platform without worrying about the computing power. In this paper first part is about introduction to character Recognition. The second part deals with the short introduction to neural network implementation for image processing using MATLAB.