Algorithm for segmenting script-dependant portion in a bilingual Optical Character Recognition system

Abstract

Documents may contain multiscript and recognition of those documents is really a challenging task. Earlier OCR (Optical Character Recognition) was developed for documents containing only English or regional languages. Documents containing multiple scripts are also needed to be kept protected for later use. So it needs more effort of the OCR designers for improving the accuracy rate for multi script OCR. In this paper we describe the character recognition process for printed documents containing Roman and Odia texts. The separation of the script has been performed at line level. We discuss a detailed description on the segmentation scheme using X-Y-Cut algorithm which isolates the text image into individual Odia and Roman line. To distinguish between the Roman and the Odia script, along with line height, we have considered the features of both the scripts. Most of the Roman character is linear as well as circular in nature and Odia characters are circular occupying more width as compared to Roman characters. We emphasize on Upper and lower Matras associated with Odia and absent in English. After extracting the individual scripts from the bilingual documents line wise, we send them to their individual OCR for recognition. Thus an algorithm has been proposed for identification of Odia and Roman scripts.