Script classification at word level for a Multilingual Document

  • Ankur Gupta et. al

Abstract

India is a multilingual multi-script country. In every state of India there are two languages one is state local language and the other is English. For example in Andhra Pradesh, a state in India, the document may contain text words in English and Telugu script. For Optical Character Recognition (OCR) of such a bilingual document, it is necessary to identify the script before feeding the text words to the OCRs of individual scripts. In this paper, we are introducing a simple and efficient technique of script identification for Kannada, English and Hindi text words of a printed document. The proposed approach is based on the horizontal projection profile for the discrimination of the three scripts. The feature extraction is done based on the horizontal projection profile of each text words. We analysed 500 different words of Kannada, English and Hindi in order to extract the discrimination features and for the development of knowledge base. We use the horizontal projection profile of each text word and based on the horizontal projection profile we extract the appropriate features. The proposed system is tested on 18 different document images containing about 400 text words of each script and a classification rate of 96.25%, 99.25% and 98.87% is achieved for Kannada, English and Hindi respectively.

 

Published
2019-11-14
How to Cite
et. al, A. G. (2019). Script classification at word level for a Multilingual Document. International Journal of Advanced Science and Technology, 28(20), 1247 - 1252. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/3835
Section
Articles