Ancient Tamil inscription recognition using detect, recognize and labelling, interpreter framework of text method
Abstract Tamil is the oldest language spoken in Tamil Nadu, India, with inscriptions dating back to the third century BCE found in caves, temples, and archaeological sites. The style and content of these inscriptions have evolved over time, reflecting changes in society, governance, and language usa...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-12-01
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| Series: | Heritage Science |
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| Online Access: | https://doi.org/10.1186/s40494-024-01522-9 |
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| author | Balasubramanian Murugan P. Visalakshi |
| author_facet | Balasubramanian Murugan P. Visalakshi |
| author_sort | Balasubramanian Murugan |
| collection | DOAJ |
| description | Abstract Tamil is the oldest language spoken in Tamil Nadu, India, with inscriptions dating back to the third century BCE found in caves, temples, and archaeological sites. The style and content of these inscriptions have evolved over time, reflecting changes in society, governance, and language usage. They provide valuable insights into rulers, dynasties, administrative systems, religious practices, and societal norms of their era. However, the diverse fonts and styles of these inscriptions necessitate an efficient method for alphabet and word recognition. Existing algorithms primarily recognize Tamil words and characters from the nineteenth century and do not address the language and styles used in the third century. This study proposes a novel DR-LIFT framework specifically designed for recognizing Tamil inscriptions from this earlier period, overcoming the limitations of current methods. The dataset used consists of third-century Tamil inscriptions. The algorithms within the DR-LIFT method specifically designed to detect text with intricate features such as curves, loops, and lines, significantly enhancing detection accuracy. The proposed framework achieves impressive outcomes, with a recognition accuracy of 99% and a recognition rate of 98.8%. |
| format | Article |
| id | doaj-art-1644eefee8ec4351903e3fd49e14a99b |
| institution | Kabale University |
| issn | 2050-7445 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Heritage Science |
| spelling | doaj-art-1644eefee8ec4351903e3fd49e14a99b2025-01-05T12:42:58ZengSpringerOpenHeritage Science2050-74452024-12-0112112110.1186/s40494-024-01522-9Ancient Tamil inscription recognition using detect, recognize and labelling, interpreter framework of text methodBalasubramanian Murugan0P. Visalakshi1Department of Networking and Communications, SRM Institute of Science and TechnologyDepartment of Networking and Communications, SRM Institute of Science and TechnologyAbstract Tamil is the oldest language spoken in Tamil Nadu, India, with inscriptions dating back to the third century BCE found in caves, temples, and archaeological sites. The style and content of these inscriptions have evolved over time, reflecting changes in society, governance, and language usage. They provide valuable insights into rulers, dynasties, administrative systems, religious practices, and societal norms of their era. However, the diverse fonts and styles of these inscriptions necessitate an efficient method for alphabet and word recognition. Existing algorithms primarily recognize Tamil words and characters from the nineteenth century and do not address the language and styles used in the third century. This study proposes a novel DR-LIFT framework specifically designed for recognizing Tamil inscriptions from this earlier period, overcoming the limitations of current methods. The dataset used consists of third-century Tamil inscriptions. The algorithms within the DR-LIFT method specifically designed to detect text with intricate features such as curves, loops, and lines, significantly enhancing detection accuracy. The proposed framework achieves impressive outcomes, with a recognition accuracy of 99% and a recognition rate of 98.8%.https://doi.org/10.1186/s40494-024-01522-9Ancient inscriptionsBhramiVattezhuthuGraph neural networkCharacter recognitionLabelling |
| spellingShingle | Balasubramanian Murugan P. Visalakshi Ancient Tamil inscription recognition using detect, recognize and labelling, interpreter framework of text method Heritage Science Ancient inscriptions Bhrami Vattezhuthu Graph neural network Character recognition Labelling |
| title | Ancient Tamil inscription recognition using detect, recognize and labelling, interpreter framework of text method |
| title_full | Ancient Tamil inscription recognition using detect, recognize and labelling, interpreter framework of text method |
| title_fullStr | Ancient Tamil inscription recognition using detect, recognize and labelling, interpreter framework of text method |
| title_full_unstemmed | Ancient Tamil inscription recognition using detect, recognize and labelling, interpreter framework of text method |
| title_short | Ancient Tamil inscription recognition using detect, recognize and labelling, interpreter framework of text method |
| title_sort | ancient tamil inscription recognition using detect recognize and labelling interpreter framework of text method |
| topic | Ancient inscriptions Bhrami Vattezhuthu Graph neural network Character recognition Labelling |
| url | https://doi.org/10.1186/s40494-024-01522-9 |
| work_keys_str_mv | AT balasubramanianmurugan ancienttamilinscriptionrecognitionusingdetectrecognizeandlabellinginterpreterframeworkoftextmethod AT pvisalakshi ancienttamilinscriptionrecognitionusingdetectrecognizeandlabellinginterpreterframeworkoftextmethod |