Optical Character Recognition

This paper describes two implementations in optical character recognition using template matching method and feature extraction method followed by support vector machine classification. With proper image preprocessing, the texts are segmented into isolated characters and the correlations between a single character and a given set of templates are computed to find the similarities and then identify the input character. In the second method, features extracted from the segmented characters are used to train the SVM classifiers, which are later, tested by a test set of handwritten digits. Keywords—Optical character recognition; template matching; feature extraction; support vector machine.