EFFICIENT ALGORITHMS FOR KANNADA AND ENGLISH SCRIPT IDENTIFICATION

Script identification is required for a multilingual OCR system. In this paper, we present a novel and efficient technique for Kannada/English script identification. The proposed approach is based upon the analysis of Kannada pages and English pages. Experimental results demonstrate that the proposed techniques are capable of identifying Kannada/English scripts from the real handwritten Kannada and English pages . Key wordsKannada script, English script, filled images, cut images, features Advances in Computational Research ISSN: 0975-3273 & E-ISSN: 0975-9085, Volume 4, Issue 1, 2012 Introduction Script Identification is part of Character recognition and the character recognition is the important area in image processing and pattern recognition fields. Automatic script identification plays an important role in processing large volumes of documents of unknown origin. In addition, the ability to reliably identify script using the least amount of textual data is essential when dealing with document pages that contain multiple languages. Since script analysis takes place prior to the actual text recognition, it cannot rely on character identification and ideally should consume only a small fraction of the total processing time. The aim of character recognition is to translate human readable characters to machine readable characters. Handwritten character recognition (HCR) has received extensive attention in academic and production fields. Handwritten documents present two challenges for script identification. First handwriting styles are more diverse than printed fonts. Cultural differences, individual differences, and even differences in the way that people write at different times, enlarge the inventory of possible character and word shapes seen in handwritten documents. Third, problems typically addressed in preprocessing, such as ruling lines and character fragmentation due to low contrast, are common in handwritten documents due to the variety of papers and writing instruments used. Lot of work is done in the recognition system. The recognition system can be either on-line or off-line. In on-line handwriting recognition words are generally written on a pressure sensitive surface (digital tablet PCs) from which real time information, such as the order of the stroke made by the writer is obtained and preserved. This is significantly different to off-line handwriting recognition where no dynamic information is available [1]. Off-line handwriting recognition is the process of identifying script from the various document images. It is the subfield of optical character recognition (OCR). Several methods of recognition of English, Latin, Arabic, Chinese scripts are excellently reviewed in [1, 2, 3, 4]. This paper is organized as follows. The section 2 describes the overview of Kannada Language The section 3 describes Data collection and discriminating features of Kannada and English Scripts. The section 4 describes proposed techniques for identifying the scripts, respective algorithms and the results obtained. Conclusion is given in section 5. Overview of Kannada Scripts In this section, we will explain the properties of popular South Indian scripts. Most of the Indian scripts are originated from Citation: Sangame S.K. , Ramteke R.J. and Gundge Y.V. (2012) Efficient Algorithms for Kannada and English Script Identification. Advances in Computational Research, ISSN: 0975-3273 & E-ISSN: 0975-9085, Volume 4, Issue 1, pp.-54-56. Copyright: Copyright©2012 Sangame S.K. , et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.