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Analyzing State-of-the-Art Techniques for Fusion of Multimodal Biometrics

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Proceedings of the Second International Conference on Computer and Communication Technologies

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 381))

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Abstract

Multimodal systems used for face recognition can be broadly classified into three categories: score level fusion, decision level fusion, and feature level fusion. In this paper, we have analyzed the performance of the three categories on various standard public databases such as Biosecure DS2, FERET, VidTIMIT, AT&T, USTB I, USTB II, RUsign, and KVKR. From our analysis, we found that score level fusion approach can effectively fuse multiple biometric modalities, and is robust to operate in less constrained conditions. In the decision fusion scheme, each decision is made after the improvement of the classifier confidence hence the recognition rate obtained is less compared to score level fusion. Feature level fusion requires less information and performs better than decision level fusion, but its recognition rate is less compared to score level fusion.

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Acknowledgments

The proposed work was made possible because of the grant provided by Vision Group Science and Technology (VGST), Department of Information Technology, Biotechnology and Science and Technology, Government of Karnataka, Grant No. VGST/SMYSR/GRD-402/2014-15 and the support provided by Department of Electronics and Communication Engineering, Karunya University, Coimbatore, Tamil Nadu, India.

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Authors and Affiliations

  1. Department Electronics and Communication Engineering, Karunya University, Coimbatore, India

    Steven Lawrence Fernandes & G. Josemin Bala

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  1. Steven Lawrence Fernandes
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  2. G. Josemin Bala
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Corresponding author

Correspondence to Steven Lawrence Fernandes .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, India

    Suresh Chandra Satapathy

  2. Department of CSE, CMR Technical Campus, Hyderabad, India

    K. Srujan Raju

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Electronics and Communication, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

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Fernandes, S.L., Josemin Bala, G. (2016). Analyzing State-of-the-Art Techniques for Fusion of Multimodal Biometrics. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 381. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2526-3_49

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  • DOI: https://doi.org/10.1007/978-81-322-2526-3_49

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  • Publisher Name: Springer, New Delhi

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  • Online ISBN: 978-81-322-2526-3

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