Publication Type:

Journal Article

Source:

International Journal of Emerging Technology and Advanced Engineering, Volume 2, Number 1, p.123-131 (2012)

URL:

https://pdfs.semanticscholar.org/b781/1b70d0a9dfd7d21955626eb82006f5dbcb83.pdf

Keywords:

Biometrics, feature, Fusion, GMM, likelihood, multimodal, Score, Template, Unimodal

Abstract:

An Unimodal biometric systems, which relies only on a single trait of a person for identification is often not able to meet the desired performance. Combining multiple biometrics may enhance the performance of personal authentication system in accuracy and reliability which is adopted in multimodal biometrics. This paper describes the feature extraction techniques for three modalities viz. fingerprint, iris and face. The extracted information is stored as a template which can be fused using density based score level fusion (using GMM followed by likelihood ratio test).

Cite this Research Publication

Aravinth J. and S.Valarmathy, D., “A Novel Feature Extraction Techniques for Multimodal Score Fusion Using Density Based Gaussian Mixture Model Approach”, International Journal of Emerging Technology and Advanced Engineering, vol. 2, pp. 123-131, 2012.