πŸ“ž +91-7667918914 | βœ‰οΈ ijarcce@gmail.com
International Journal of Advanced Research in Computer and Communication Engineering
International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 3, ISSUE 3, MARCH 2014

Indian Sign Language Recognition System for Deaf People

ARTI THORAT, VARSHA SATPUTE, ARATI NEHE, TEJASHRI ATRE YOGESH R NGARGOJE BE Student,CSE Department, Savitribai Phule Womens Engineering College, Sharanapur, Aurangabad, India BE Student,CSE Department, Savitribai Phule Womens Engineering College, Sharanapur, Aurangabad, India BE Student,CSE Department, Savitribai Phule Womens Engineering College, Sharanapur, Aurangabad, India BE Student,CSE Department, Savitribai Phule Womens Engineering College, Sharanapur, Aurangabad, India Assistant Professor

πŸ‘ 45 viewsπŸ“₯ 0 downloads
Share: 𝕏 f in ✈ βœ‰
Abstract: Sign Language Recognition System is one of the most growing researches today. Many new Techniques are having been developed recently in the field of Sign Language Recognition. This system becomes popular because it is only one of the efficient way through which the deaf and dumb people can convey their message to other people. In this paper we proposed some methods, through which the recognition of the signs becomes easy. We use the different signs to convey the meanings. And the result of those signs will be converted into the text. We proposed a method for that is, Scale Invariance Fourier Transform (SIFT).By using the Webcam we capture the image of the hand gesture, after that by using SIFT algorithm, Feature Extraction will performed. That matches the key points of captured image with key points of previously stored images

Keywords: Indian Sign Language, Feature Extraction, Edge Detection, Sign recognition, Color, Texture.

How to Cite:

[1] ARTI THORAT, VARSHA SATPUTE, ARATI NEHE, TEJASHRI ATRE YOGESH R NGARGOJE BE Student,CSE Department, Savitribai Phule Womens Engineering College, Sharanapur, Aurangabad, India BE Student,CSE Department, Savitribai Phule Womens Engineering College, Sharanapur, Aurangabad, India BE Student,CSE Department, Savitribai Phule Womens Engineering College, Sharanapur, Aurangabad, India BE Student,CSE Department, Savitribai Phule Womens Engineering College, Sharanapur, Aurangabad, India Assistant Professor, β€œIndian Sign Language Recognition System for Deaf People,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE)

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.