Individual authentication through hand posture recognition using Multi-Hilbert Scanning Distance

Author

Ryu, Jegoon ; Kamata, Sei-ichiro

Author_Institution

Grad. Sch. of Inf., Waseda Univ., Kitakyushu, Japan

fYear

2012

Firstpage

1787

Lastpage

1790

Abstract

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.

Keywords

feature extraction; image matching; mathematical analysis; palmprint recognition; HPR; MHSD; biometrics; feature descriptor extraction; hand pose alignment; individual authentication; mathematical approaches; multiHilbert scanning distance; robust hand posture recognition; shape matching; three dimensional point clouds; Bifurcation; Biometrics (access control); Feature extraction; Shape; Skeleton; Vectors; Wrist; Biometrics; Hand Posture Recognition (HPR); Hilbert Scanning; Multi-Hilbert Scanning Distance (MHSD);

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European

ISSN

2219-5491

Print_ISBN

978-1-4673-1068-0

Type

conf

Filename

6334165