ISSN (Print) : 2320 – 9798 ISSN (Online): 2320 – 9801 International Journal of Innovative Research in Computer and Communication Engineering Vol. 1, Issue 4, June 2013 Copyright to IJIRCCE www.ijircce.com 1056 RECOGNITION OF DISTORTED CHARACTER USING EDGE DETECTION ALGORITHM S.K.Thilagavathy 1 and Dr.R.Indra Gandhi 2 Research Scholar, Department of Computer Applications, GKM College of Engineering and Technology, Chennai, 1 Professor, Department of Computer Applications, GKM College of Engineering and Technology, Chennai, Tamil India 2 ABSTRACT: Character recognition is an ever ending research application in the real world. Each character recognition should be accurate. So that it leads to understand the exact meaning and concept. Analyzing the distorted character is quite complicated work. In some unique languages like Tamil, Telugu and Malayalam the distorted character may resemble like some other character. In this paper analysis of each character is done even though it is inconsistent in shape and irrespectively distorted. KEYWORDS: Character recognition, OCR, Edge Detection Algorithm 1. INTRODUCTION Optical character recognition has become one of the most successful applications of technology in the field of pattern recognition and artificial intelligence. Both hand written and printed characters may be recognized, but the performance is directly dependent upon the quality of the input documents. Recognized characters which are inconsistency in shape and Irrespective of distortions are reproducing the actual characters from distorted documents based on algorithms and methods. And the steps involved in character recognition comprise pre-processing, segmentation feature extraction and classification. 2. REVIEW OF LITERATURE According to the Line Eikvil Optical Character Recognition deals with the problem of recognizing optically processed characters. Optical recognition is performed off-line after the writing or printing has been completed, as opposed to on-line recognition where the computer recognizes the characters as they are drawn. Both hand printed and printed characters may be identified, but the performance is pursuance dependent upon the quality of the input documents. The Character recognition is classified into On-line and Off-line. The off-line is further as Single characters and Handwritten script. The Single character is divided into Printed and Handwritten. Like wise handwritten script is divided into Recognition and Verification[1]. The idea behind an OCR is to identify and analyses of a document image by dividing the page into line elements, further sub-dividing into words, and then into characters. These characters are compared with image patterns to state the probable characters. And particularly in Tamil handwritten OCR is more complicated than other related works. This is because Tamil letters have more angles and modifiers[2]. Recognition system works well for simple language like English. It has only 26 character sets. And for standard text there are 52 numbers of characters including capital and small letters. But a complex but organized language like Telugu, OCR system is still in introductory level [3]. But Dyashankar Singh, Sajay Kr. Singh and Dr.MitreyeeDutta speaks about that Character recognition process is dependent upon number of factors like various font sizes, noise, broken lines or characters etc. and these factors influence the results of recognition system[4].Based on the zone-wise character are also classified and identified. [5].Many diverse algorithms /schemes for handwritten character recognition[6,7] exist and each of these has its own merits and demerits. Some of them used Back Propagation Algorithm[8,9,10], Template matching algorithm [11] and structural analysis [11,12]etc. Here I had used the Edge Detection Algorithm to reproduce the accurate character from the distorted character.