A Novel Technique to Enhance Performance of Multibiometric Framework using Bin based Classifier Based on Multi-algorithm Score Level Fusion
Sandip Kumar Singh Modak1, Vijay Kumar Jha2

1Sandip Kumar Singh Modak*, Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, India.
2Vijay Kumar Jha, Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, India.
Manuscript received on December 16, 2019. | Revised Manuscript received on December 22, 2019. | Manuscript published on January 10, 2020. | PP: 2156-2166 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8773019320/2020©BEIESP | DOI: 10.35940/ijitee.C8773.019320
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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: This work shows a multibiometric framework to upgrade the recognition rate and reduce the error rate using Bin based classifier based on score level (multi-algorithm) fusion. In this work Bin based classifier is used as the combination rule which integrate the matching scores from two distinct modalities namely iris and face. An optimization technique, PSO is utilized to minimize the unwanted information after combination of the feature sets of the iris and face using different feature extraction algorithms like PCA, LDA and LBP. The test results demonstrate that the multibiometric system as a Bin based classifier employing multi-algorithm score level fusion provides better outcomes than the other fusion rule like Likelihood Ratio based fusion, Linear Discriminant Analysis (LDA) and support vector machine (SVM). The experimental result on Face (ORL, BANCA,FERET) and iris (CASIA, UBIRIS) shows that the proposed multimodal system derived from CBBC (continuous bin based classifier) with PSO as an optimization technique achieve EER=0.012 , which outperform than the other fusion technique with EER=0.018 for SVM (RBF) and EER=0.02 for SVM linear. 
Keywords: Multibiometric, Multi-Algorithm, Face, Iris, Score Level Fusion, Support Vector Machine, Particle Swarm Optimization, and Continuous Bin Based Classifier.
Scope of the Article: Algorithm Engineering