Feature Level Fusion of Iris and Finger Vein Biometrics for Multimodal Biometric Authentication System
Sudhamani M J1, M K Venkatesha2
1Sudhamani M J, RNS Institute of Technology, Bengaluru, (Karnataka), India .
2M K Venkatesha, RNS Institute of Technology, Bengaluru, (Karnataka), India.
Manuscript received on 24 January 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 January 2019 | PP: 132-139 | Volume-7 Issue-6, March 2019 | Retrieval Number: E2114017519©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With the intense need of security, a reliable authentication system can be attained using multimodal biometrics. Predominately vein patterns are attracting the researchers for developing authentication system. Multimodal biometric system not only aims at combining traits but also on fusion at various levels. Proposed approach fuses invariant iris features and finger vein shape features. The fusion at feature level framework is evaluated to perceive classification accuracy of biometric authentication system. Algorithm prioritizes on reducing high dimension features by considering iris Hu moments and finger vein shape features to accomplish a secured and convenient authentication system. SVM Classifier results prove that multimodal biometric outperforms compared to Uni-modal system.
Keywords: Biometrics, Feature Fusion, Hu moment, Multimodal, Shape Features
Scope of the Article: System Integration