Lipi Gnani: A Versatile OCR for Documents in any Language Printed in Kannada Script

Kumar, HRS and Ramakrishnan, AG (2020) Lipi Gnani: A Versatile OCR for Documents in any Language Printed in Kannada Script. In: ACM Transactions on Asian and Low-Resource Language Information Processing, 19 (4).

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Abstract

A Kannada OCR, called Lipi Gnani, has been designed and developed from scratch, with the motivation of it being able to convert printed text or poetry in Kannada script, without any restriction on vocabulary. The training and test sets have been collected from more than 35 books published from 1970 to 2002, and this includes books written in Halegannada and pages containing Sanskrit slokas written in Kannada script. The coverage of the OCR is nearly complete in the sense that it recognizes all punctuation marks, special symbols, and Indo-Arabic and Kannada numerals. Several minor and major original contributions have been done in developing this OCR at different processing stages, such as binarization, character segmentation, recognition, and Unicode mapping. This has created a Kannada OCR that performs as good as, and in some cases better than, Google's Tesseract OCR, as shown by the results. To the best of our knowledge, this is the maiden report of a complete Kannada OCR, handling all issues involved. Currently, there is no dictionary-based postprocessing, and the obtained results are due solely to the recognition process. Four benchmark test databases containing scanned pages from books in Kannada, Sanskrit, Konkani, and Tulu languages, but all of them printed in Kannada script, have been created. The word-level recognition accuracy of Lipi Gnani is 5.3 higher on the Kannada dataset than that of Google's Tesseract OCR, 8.5 higher on the Sanskrit dataset, and 23.4 higher on the datasets of Konkani and Tulu. © 2020 ACM.

Item Type:	Journal Article
Publication:	ACM Transactions on Asian and Low-Resource Language Information Processing
Publisher:	Association for Computing Machinery
Additional Information:	Copyright for this article belongs to Association for Computing Machinery
Keywords:	Agricultural engineering; Natural resources, Benchmark tests; Character segmentation; Kannada scripts; Processing stage; Punctuation marks; Recognition accuracy; Recognition process; Special symbols, Benchmarking
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	05 Nov 2020 10:02
Last Modified:	05 Nov 2020 10:02
URI:	http://eprints.iisc.ac.in/id/eprint/66996

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