Developing a Prototype Hand Gesture Recognition System in Interpreting American Sign Language
K.S. Chong, Kasthuri Subaramaniam, Ismail Ahmed Al-Qasem Al-Hadi · Proceedings of International Conference on Artificial Life and Robotics · 2024
Hand gestures of sign language is a form of non-verbal communication which have been used by most people in their daily life.Sign language is not only used by people with speaking issues but it is also unconsciously used by normal people during their daily interaction with others.This is because it is a way to express their current feelings or the meaning they wanted to convey to others.On other hand, sign language is an important alternative used by people with hearing impairment or speaking obstacles so they can communicate with others.However, not everyone from all walks of life has learned sign language so there will be problems of interaction between them and people with speaking issues.Thus, this research focuses on developing a hand gesture recognition system for accurately interpreting American Sign Language (ASL) so that it can deliver a message that can be understood by others and enable efficient communication.In our system, it will utilize computer vision techniques to analyze hand postures and movements which will include hand sign recognition, finger tracking, and motion estimation.With the pre-developed libraries like OpenCV and MediaPipe are employed in the system so it can recognize and classify ASL gestures based on extracted features.Extensive datasets of ASL hand gestures are collected and annotated to enhance the system's accuracy and robustness.The developed system aims to improve human-computer interaction, enabling seamless communication between deaf individuals and technology.The potential applications include real-time interpretation of ASL gestures for enhanced accessibility and inclusivity.