DocumentCode
3360497
Title
Automated hand shape verification using HMM
Author
Dong-Mei, Sun ; Zheng-Ding, Qiu
Author_Institution
Inst. of Inf. Sci., Northern Jiaotong Univ., Beijing, China
Volume
3
fYear
2004
fDate
31 Aug.-4 Sept. 2004
Firstpage
2274
Abstract
In this paper we present a method for identity verification based on matching of hand shapes. Our method first represents the shapes of hands by sets of ordered points. Then the contour of the hand is characterized by a features sequence consisting of two parameters: the radius and curvature at the contour points, MMM has proved a very successful tool for modeling and recognition sequence signal. So the hand shapes are compared using HMM. We apply a normalization score measurement to improve the classification ability and robustness. The experiment results show the effectiveness of our method and the correct verification rate can be above 90%.
Keywords
hidden Markov models; image classification; image matching; image sequences; automated hand shape verification; contour points; features sequence; hand shape matching; normalization score measurement; recognition sequence signal; Biometrics; Fingerprint recognition; Fingers; Hidden Markov models; Iris; Retina; Robust control; Shape control; Size control; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN
0-7803-8406-7
Type
conf
DOI
10.1109/ICOSP.2004.1442233
Filename
1442233
Link To Document