User Independent System for Recognition of Hand Postures Used in Sign Language

Abstract

A new signer independent method of recognition of hand postures of sign language alphabet is presented in this paper. We propose a new geometric hand postures features derived from the convex hull enclosing the hand's shape. These features are combined with the discrete orthogonal Tchebichef moments, and the Hu moments. The Tchebichef moments are applied on the external and internal edges of the hand's shape. Experiments, based on two different hand posture data sets, show that our method is robust at recognizing hand postures independent of the person performing them. The system obtains a good recognition rates, and also performs well compared to other hand user independent posture recognition systems.