Optical Character Recognition using Template Matching and Back Propagation Algorithm

Abstract

Building an effective methodology to detect characters from images with less error rate is the challenging task. Our aim is to furnish such an algorithm that will be able to generate error free recognition of text from the given input image. It will help in document digitizing and prevention to the hand written text recognition. OCR has been in the intensive research topic for more than 4 decades. It is probably the most time consuming and labour intensive work of inputting the data through keyboard .This thesis discuss about mechanical or electronic conversion of scanned images. Text which contain graphics, image captured by camera, scanned images and the recognition of images where characters may be broken or smeared .The optical character recognition is the desktop based application developed using Java IDE and mysql as a database . We managed to reach the accuracy of 91.82% accuracy when applied (IBPTM) on different data sets. In pre-processing module we have used different techniques to remove noise from the image; while post processing we used dictionary module for the characters which are not recognized during classification; in classification module we have used the back propagation algorithm for the training of neural network. Feature extraction has been performed by template matching and hamming distance. All the algorithms have been developed in java technology.