TFRS: Thai finger-spelling sign language recognition system

Thai Sign Language has been a research priority since most people do not understand sign language, making it almost impossible to have daily-life communication with people who are deaf or mute. Past research works in Thai Sign Language Recognition which employs image processing techniques still do not perform well due to its limitation in similar hand image extraction of key features. To alleviate the problems and to improve its performance, this paper proposes Thai sign language recognition system using data gloves and a motion tracker device. Our focus is primarily alphabetic finger-spelling of Thai sign language by recognizing single-gesture hand shapes. Data segmentation and Neural Network techniques are utilized to improve the accuracy of the system.