Open AccessRecognition of Sign Language Based on Hand Gestures
Author(s) -
Gunji Bala Murali,
Nikhil M. Bhargav,
Arun K. Dey,
Isahak Karajagi Zeeshan Mohammed,
Sachdev Sathyajith
Publication year - 2022
Publication title -
journal of advances in applied and computational mathematics
Language(s) - English
Resource type - Journals
ISSN - 2409-5761
DOI - 10.15377/2409-5761.2021.08.3
Subject(s) - sign language , gesture , sign (mathematics) , computer science , gesture recognition , motion (physics) , set (abstract data type) , artificial intelligence , natural language processing , speech recognition , linguistics , mathematics , programming language , mathematical analysis , philosophy
The target of SLR or sign language recognition is to interpret the sign language into text, respectively. So the deaf and mute people can communicate with ordinary people easily. Sign language recognition has a tremendous social impact; however, it is challenging due to the significant variations and complexity in the hand actions. There are many existing methods for recognizing sign language that uses handcraft features for describing the motion of sign language and then, based on the features it makes the classification models. To approach the problem, we have discussed considering the KNN that can conveniently extract the features. The proposed model can be validated on a real data set.