TEXT RECOGNITION FROM IMAGES USING IMAGE PROCESSING TECHNIQUE

Abstract

— Image Processing is a next level character and object recognizer. At present image processing is a major technology that evolved in order to identify things as same as human eyes. It is developed by using a trained model in order to capture objects optically, it has greater error rate in order to capture the character and objects. Nowadays it is popularly used everywhere in various businesses and software tools. A paper document is best source of raw data but filtering required information from it is difficult. In order to gather in such a way, we need information into textual document which easily underpass into filters and produces required output from it. Image processing algorithms are not accurate enough to give efficient output of the text document. It can be improved by using trained model which frequently updates the algorithm efficiency and in order to decrease the word error rate. In this way text can be recognized efficiently from the image. The major distractors in this are image quality, image contrast, pixel level impurities and image backgrounds acts a lot in text recognition. Various improvements are brought in order to get the best out of the image content.