Static hand gesture recognition for vietnamese sign language (VSL) using principle components analysis

Nowadays, hand gesture is one of main considerations for hearing impaired people because they use sign language to communicate with each other and to normal people. In general, the normal people have difficulties with sign language therefore they need an interpreter supporting communication. Then the automatic hand gesture recognition system is needed to help hearing impaired people integrating into social community. In technical, sign language is comprehensive problem because the complexity of visual analysis of hand gesture and the highly structured nature of sign language. This paper proposes a system using Principle Component Analysis (PCA) to recognize hand gestures for Vietnamese Sign Language (VSL) in uniform background and evaluate the effectiveness of methods using Euclidean and Mahalanobis distance in classification. The experimental results show that the proposed method obtains a high success rate in recognition.