Kannada Characters Recognition - A Novel Approach Using Image Zoning and Run Length Count

TitleKannada Characters Recognition - A Novel Approach Using Image Zoning and Run Length Count
Publication TypeJournal Article
Year of Publication2011
AuthorsKarthik S., Mamatha HR, Murthy SK
JournalCiiT International Journal of Digital Image Processing
Volume3
Issue16
Pagination1059-1062
KeywordsDepartment of Information Science and Engineering
Abstract

Optical Character Recognition (OCR) is one of the important field in image processing and pattern recognition domain. Many practical applications uses OCR with high accuracy. The accuracy of the Optical Character Recognition system depends on the quality of the features extracted and the effectiveness of the classifier. Here we are proposing a novel method to recognize the printed kannada vowels. Kannada script has large number of characters having similar shapes and also the complexity is font dependent, which means the same characters in a class, may vary in structure for different fonts. Hence a method, which makes use of image zoning and the Run Length Count techniques to extract the features have been proposed. The methodology uses Naive Bayes classifier, K-Nearest Neighbor classifier for classification. The method experimented on a dataset, which consists of samples from 69 different fonts, and a maximum of 97.44% recognition accuracy is achieved

URLhttp://ciitresearch.org/dl/index.php/dip/article/view/DIP102011026