Authors:
Dahmani Djamila
;
Benchikh Soumia
and
Slimane Larabi
Affiliation:
University of Science and Technology Houari-Boumedienne, Algeria
Keyword(s):
Hand posture recognition, Moments, Shape, Sign language.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Human-Computer Interaction
;
Image Understanding
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Object Recognition
;
Pattern Recognition
;
Physiological Computing Systems
;
Shape Representation
;
Software Engineering
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.