LANGUAGE IN INDIA

Strength for Today and Bright Hope for Tomorrow

Volume 14:9 September 2014
ISSN 1930-2940

Managing Editor: M. S. Thirumalai, Ph.D.
Editors: B. Mallikarjun, Ph.D.
         Sam Mohanlal, Ph.D.
         B. A. Sharada, Ph.D.
         A. R. Fatihi, Ph.D.
         Lakhan Gusain, Ph.D.
         Jennifer Marie Bayer, Ph.D.
         S. M. Ravichandran, Ph.D.
         G. Baskaran, Ph.D.
         L. Ramamoorthy, Ph.D.
         C. Subburaman, Ph.D. (Economics)
Assistant Managing Editor: Swarna Thirumalai, M.A.

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Efficient Recognition of Telugu Characters
Based on Critical Points Generated
Using Morphological Methods

Ramalingeswara Rao K V
Bhaskara Rao N
Ramesh Babu D R


Abstract

A novel method for recognition of telugu character is proposed in this paper. The proposed method uses extraction of critical points of the characters based on grid and radial intersections analysis. The extracted critical points are classified based on the grid and radial lines, which helps in improving accuracy in recognition of characters. The algorithm is tested on various data sets and the results are satisfactory. The technique is a generic method in the sense that it is applicable for all Indian language scripts like Sanskrit, Hindi, Telugu, Kannada, Tamil, Malayalam, etc.

Index Terms — Indian Languages, Grid based Intersecting Points Analysis, Radial Axis based Intersecting Points Analysis, Critical Points Analysis, Morphological Feature Extraction Methods, Optical Character Recognition.

1. Introduction

Optical Character Recognition (OCR) is the mechanical or electronic conversion process of scanned printed or handwritten text images into computer-readable text format. It is a common method of digitization of printed/handwritten text documents. The digitized data can be electronically edited, searched, stored more compactly, displayed on-line, and also, it can be used for data extraction, language translation, text-to-speech conversion and data mining. OCR is used in many applications such as script recognition, language identification, postal processing, banking, and security check with the Authentication of Unique Identification Documents (for example, Aadhaar Card, Passport, PAN Card, Driving License, etc.) [1]. Nowadays, many organizations are giving high preference to OCR systems to minimize the human interactions for better performance and efficiency. OCR can be applied with the help of Pattern Recognition and/or Artificial Intelligence techniques to achieve accurate results. Generally, OCR system goes through various phases including: data collection, pre-processing, feature extraction, classification and post-processing [2].


This is only the beginning part of the article. PLEASE CLICK HERE TO READ THE ENTIRE ARTICLE IN PRINTER-FRIENDLY VERSION.


Mr. Ramalingeswara Rao K V, M.C.A., M.Phil.
Research Scholar
Dravidian University
Kuppam - 517 425
Andhra Pradesh
India
kvramalingeswararao@gmail.com

Prof. Bhaskara Rao N, M.Tech.
Professor, Computer Science & Engineering
Dayananda Sagar College of Engineering
Bangalore - 560078
Karnataka
India
bhaskararao.nadahalli@gmail.com

Dr. Ramesh Babu D R, M.Tech., Ph.D.
Professor, Computer Science & Engineering
Dayananda Sagar College of Engineering
Bangalore - 560078
Karnataka
India
bobrammysore@gmail.com

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