NDLI: A single-sensor hand geometry and palmprint verification system

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A single-sensor hand geometry and palmprint verification system

Content Provider	ACM Digital Library
Author	Ling, David Ngo Chek Ong, Michael Goh Kah Connie, Tee Jin, Andrew Teoh Beng
Abstract	Several contributions have shown that fusion of decisions or scores obtained from various single-modal biometrics verification systems often enhances the overall system performance. A recent approach of multimodal biometric systems with the use of single sensor has received significant attention among researchers. In this paper, a combination of hand geometry and palmprint verification system is being developed. This system uses a scanner as sole sensor to obtain the hands images. First, the hand geometry verification system performs the feature extraction to obtain the geometrical information of the fingers and palm. Second, the region of interest (ROI) is detected and cropped by palmprint verification system. This ROI acts as the base for palmprint feature extraction by using Linear Discriminant Analysis (LDA). Lastly, the matching scores of the two individual classifiers is fused by several fusion algorithms namely sum rule, weighted sum rule and Support Vector Machine (SVM). The results of the fusion algorithms are being compared with the outcomes of the individual palm and hand geometry classifiers. We are able to show that fusion using SVM with Radial Basis Function (RBF) kernel has outperformed other combined and individual classifiers.
Starting Page	100
Ending Page	106
Page Count	7
File Format	PDF
ISBN	1581137796
DOI	10.1145/982507.982526
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2003-11-08
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Multimodal biometric Hand geometry Fusion Palmprint
Content Type	Text
Resource Type	Article

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