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Abstract
In the field of electronics and image processing; computer vision, artificial intelligence and pattern recognition has a great significance. Optical character recognition (OCR) has evolved a lot since the beginning and is one of the important aspects of pattern recognition. OCR converts the optical data, which is recognized from the readable characters into the digital form. Different approaches are clubbed with various methodologies for this purpose. In this paper, we are going to recognize optical characters using a very famous machine learning technique, Support Vector Machine. SVM is a very powerful black box testing algorithm which classifies data by creating a hyperplane or line. The main reason for such programming is to process paper based records by changing over printed or written by hand message into an electronic structure to be spared in a database. In this paper we are going to recognize optical character using SVM for different kernel parameters.