Publication Type : Journal Article
Publisher : International Journal of Emerging Technology and Advanced Engineering
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
Campus : Coimbatore
School : School of Engineering
Department : Electronics and Communication
Year : 2012
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.