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Generation of new points for training set and feature-level fusion in multimodal biometric identification

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Abstract

Multimodal biometrics has gained interest in the recent past due to its improved recognition rate over unibiometric and unimodal systems. Fusion at feature level is considered here for the purpose of recognition. The biometrics considered for fusion are face and iris. Here, new face images along with iris images are generated, and they are included in the training set. Feature-level fusion is incorporated. The recognition rates of the classification algorithm thus obtained are statistically found to be significantly better than the existing feature-level fusion and classification techniques.

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Authors and Affiliations

  1. Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India

    Dhiman Karmakar & C. A. Murthy

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  1. Dhiman Karmakar
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  2. C. A. Murthy
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Correspondence to C. A. Murthy.

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Karmakar, D., Murthy, C.A. Generation of new points for training set and feature-level fusion in multimodal biometric identification. Machine Vision and Applications 25, 477–487 (2014). https://doi.org/10.1007/s00138-013-0532-y

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  • DOI: https://doi.org/10.1007/s00138-013-0532-y

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