Language Identification from an Indian Multilingual Document Using Profile Features

In order to reach a larger cross section of people, it is necessary that a document should be composed of text contents in different languages. But on the other hand, this causes practical difficulty in OCRing such a document, because the language type of the text should be pre-determined, before employing a particular OCR. In this research work, this problem of recognizing the language of the text content is addressed, however it is perhaps impossible to design a single recognizer which can identify a large number of scripts/languages. As a via media, in this research we have proposed to work on the prioritized requirements of a particular region, for instance in Karnataka state in India, generally any document including official ones, would contain the text in three languages-English-the language of general importance, Hindi-the language of National importance and Kannada-the language of State/Regional importance. We have proposed to learn identifying the language of the text by thoroughly understanding the nature of top and bottom profiles of the printed text lines in these three languages. Experimentation conducted involved 800 text lines for learning and 600 text lines for testing. The performance has turned out to be 95.4%.