Marathi sign language recognition methodology using Canny's edge detection.
Published In: Sādhanā: Academy Proceedings in Engineering Sciences, 2025, v. 50, n. 4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Mali, Yogesh Kisan 3 of 3
Abstract
Sign language serves as a communication tool for those who are deaf or unable of hearing or speaking. Sign language is a language where two people communicate by using their hands and motions. These people utilize hand gestures to communicate with one another since they are vocally impaired. These individuals use body language, facial expressions, and hand gestures to communicate with one another; this type of communication is sometimes referred to as sign language. Each nation has its own sign language, such as Indian Sign Language (ISL), Arabic Sign Language (ArSL), or American Sign Language (ASL), which is used for communication. The suggested system can recognize Marathi Sign Language and is implemented in Indian Sign Language. There are forty-five Marathi alphabets that are used in Marathi sign language. The goal of the suggested method is to translate or convert Marathi sign language to text and the other way around. Our technology can recognize and translate words, phrases, and the Marathi alphabet. This translation is carried out using a database that contains words and alphabets in sign language. The system is evaluated using the Marathi alphabet and vocabulary, and several deaf sign users are used for study. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Sādhanā: Academy Proceedings in Engineering Sciences. 2025/12, Vol. 50, Issue 4, p1
- Document Type:Article
- Subject Area:Communication and Mass Media
- Publication Date:2025
- ISSN:0256-2499
- DOI:10.1007/s12046-025-02963-z
- Accession Number:188851368
- Copyright Statement:Copyright of Sādhanā: Academy Proceedings in Engineering Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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