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 :
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