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Can I read Multimodal Biometric Authentication Based on Score Level Fusion Using Support Vector Machine on EtoBox?
Multimodal Biometric Authentication Based on Score Level Fusion Using Support Vector Machine by F. Wang; J. Han is a Engineering article available to read on EtoBox.
What is Multimodal Biometric Authentication Based on Score Level Fusion Using Support Vector Machine about?
Fusion of multiple biometrics for human authentication performance improvement has received considerable attention. This paper presents a novel multimodal biometric authentication method integrating face and iris based on score level fusion. For score level fusion, support vector machine (SVM) based fusion rule is applied to combine two matching scores, respectively from Laplacianface based face verifier and phase information based iris verifier, to generate a single scalar score which is used to make the final decision. Experimental results show that the performance of the proposed method can bring obvious improvement comparing to the unimodal biometric identification methods and the previous fused face-iris methods.
Who reads Multimodal Biometric Authentication Based on Score Level Fusion Using Support Vector Machine?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- F. Wang; J. Han
- Publisher
- Polish Academy of Sciences Chancellery
- Published
- 2009
- Language
- EN
- Field
- Engineering (Physical Sciences)