Sign language recognition

Abstract

In this paper, an image processing algorithm is presented for the interpretation of the Taiwanese sign language, which is one of the sign languages used by the majority of the deaf community. The process involves two layer classifications. At first, coarse classification is done according to detection of hand motion and tracking the hand location and second classification is based on key frame selection and hand shape recognition of key frames. Motion history image and Fourier descriptor are used for motion direction recognition and key frame selection respectively. Generic cosine descriptor (GCD) has been proposed for feature extraction of hand postures. GCD is invariant to scale, translation and rotation of hand shapes. Our system tests 15 different hand gestures of 10 persons. The experimental results show that our system can achieve 100% recognition rate for test persons.