Lipi Gnani
| Autor: | A. G. Ramakrishnan, H. R. Shiva Kumar |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Konkani
Vocabulary General Computer Science business.industry Computer science Character (computing) media_common.quotation_subject 020208 electrical & electronic engineering 020206 networking & telecommunications 02 engineering and technology computer.software_genre Punctuation Unicode language.human_language Numeral system 0202 electrical engineering electronic engineering information engineering language Tesseract Artificial intelligence business Sanskrit computer Natural language processing media_common |
| Zdroj: | ACM Transactions on Asian and Low-Resource Language Information Processing. 19:1-23 |
| ISSN: | 2375-4702 2375-4699 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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