Abstract
In this paper, we represent a score level fusion method on fingerprint and finger vein. Each unimodal identification system carries out processes of image preprocessing, feature extraction and feature matching to generate a vector of score. And we apply clustering analysis to split the score range into zones of interest. Then a decision tree and weighted-sum approach are used to make the decision. We test the proposed method on standard biometric database. Three metrics, namely, False Accept Rate, False Reject Rate, Recognition Rate, are used to evaluate experimental results. And experimental results show that the fusion system has a better performance than unimodal identification system.
Highlights
Biometric identification system is a prerequisite to ensure the security of the system
We do use the weighted sum method to make the fusion method more effective, and improve the fusion method which can be used among many other biometrics
The code M and code N are inferred from two finger vein images, while the mask M and mask N are the respective masks of the two images due to the blocked light
Summary
Biometric identification system is a prerequisite to ensure the security of the system. The combined method did not give a convinced demonstration about how to allocate weight to each score from unimodal identification system. After the generation of scores of matching values from each unimodal identification system, it will be the fusion process. In [8], the method achieves the classification by the decision tree combined to the weighted sum (BCC) in the paper. It generates a new score level fusion method. We do some research on it and choose the appropriate computing method which can be applied in the fusion process In this way, we do use the weighted sum method to make the fusion method more effective, and improve the fusion method which can be used among many other biometrics
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