TY - GEN
T1 - Individual authentication through hand posture recognition using Multi-Hilbert Scanning Distance
AU - Ryu, Jegoon
AU - Kamata, Sei Ichiro
PY - 2012
Y1 - 2012
N2 - In this paper, we propose a novel Hand Posture Recognition (HPR) for biometrics. This study uses the three dimensional point clouds for robust hand posture recognition at the rotation and scale. Multi-Hilbert Scanning Distance (MHSD) are also introduced for mathematical approaches of shape matching. HPR framework is divided into five parts: detecting hand region, removing the wrist, aligning the hand pose, extracting feature descriptor, and matching. Based on the experimental results, this framework showed superior results for hand posture recognition rate.
AB - In this paper, we propose a novel Hand Posture Recognition (HPR) for biometrics. This study uses the three dimensional point clouds for robust hand posture recognition at the rotation and scale. Multi-Hilbert Scanning Distance (MHSD) are also introduced for mathematical approaches of shape matching. HPR framework is divided into five parts: detecting hand region, removing the wrist, aligning the hand pose, extracting feature descriptor, and matching. Based on the experimental results, this framework showed superior results for hand posture recognition rate.
KW - Biometrics
KW - Hand Posture Recognition (HPR)
KW - Hilbert Scanning
KW - Multi-Hilbert Scanning Distance (MHSD)
UR - http://www.scopus.com/inward/record.url?scp=84869854252&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84869854252&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84869854252
SN - 9781467310680
T3 - European Signal Processing Conference
SP - 1787
EP - 1790
BT - Proceedings of the 20th European Signal Processing Conference, EUSIPCO 2012
PB - European Signal Processing Conference, EUSIPCO
T2 - 20th European Signal Processing Conference, EUSIPCO 2012
Y2 - 27 August 2012 through 31 August 2012
ER -