Robust classification of hand postures against complex backgrounds

A system for the classification of hand postures against complex backgrounds in grey-level images is presented. The system employs elastic graph matching, which has already been successfully employed for the recognition of faces. Our system reaches 86.2% correct classification on our gallery of 239 images of ten postures against complex backgrounds. The system is robust with respect to certain variations in size of hand and shape of posture.