Finger-spelling recognition system using fuzzy finger shape and hand appearance features

In this paper, we introduce a method for finger-spelling recognition system. The objective is to help the deaf or non-vocal persons to improve their skills on the finger-spelling. Many researches in this field have proposed methods mostly based on hand posture estimation techniques. We propose an alternative flexible method based on fuzzy finger shape and hand appearance analysis. By using depth image, the hand is extracted and tracked using an active contour like method. Its features, such as, finger shape, and hand appearance, have been defined as chain code, which are input to the American finger-spelling recognition system by using a vote method. The performance of the system is tested in real-time environment, which results in around 70% recognition rate.