A Hand Gesture Recognition based Communication System for Mute people

• Published in: 2020 IEEE 23rd International Multitopic Conference (INMIC) pp. 1 - 6
• Main Authors: Haider, Iram, Mehdi, Mohammad Ammar, Amin, Asjad, Nisar, Kashif
• Format: Conference Proceeding
• Language: English
• Published: IEEE 05.11.2020
• Subjects: Artificial Intelligence; Cameras; Deaf and Mute Communication; Estimation; Gesture recognition; Human computer Interaction; Image color analysis; Image segmentation; Lighting; Motion Sensors; Sign Language; Skin
• ISSN: 2049-3630
• DOI: 10.1109/INMIC50486.2020.9318072

Communication between deaf-mute people becomes more difficult in everyday life. Muteness creates a speechaffliction where the patient is unable to have the normal capacity to speak resulting in the complete absence or at least a significant loss of verbal communication under neurological diseases. Sometimes the major cause of muteness is deafness. Around 466 million people worldwide are deaf and mute, and 34 million of these are children. The communication among a deaf and listening to person poses to be an excessive hassle compared to communication among blind and regular visible humans. Gestural type of communication called Sign language which is observed amongst deaf groups in the world. We proposed a Deaf-Mute verbal exchange device that translates the hand gestures to audio massage as an interpreter. The purpose to develop this plan, is to facilitate humans with the help of a deaf-mute communication interpreter device. In the designed model, we used the KINECT sensor-based system to interpret hand gestures. The KINECT sensor captures the motions of mute people like images and then after segmentation, it identifies the gestures which are then decoded into meaningful audio messages that enable the communication more effective. The proposed system is user friendly, as it is easy to use and capable to build efficient and effective human computer interaction.