A novel multi-modal biometric authentication system with enhanced feature extraction using advanced mapped real transform

  • Authors

    • Lakshmi S Panicker School of Engineering, Cochin University of Science and Technology
    • R. Gopikakumari School of Engineering, CUSAT
    2025-01-07
    https://doi.org/10.14419/tn22a349
  • Audio-Visual Biometrics; Feature Level Fusion; SMRT.

  • Abstract

    In contexts where security is a top priority, biometric authentication, which is the act of identifying a person using physiological or behavioral modalities—acquires critical importance. Facial image and speech are the two most popular biometrics for personal verification. This paper introduces a new audio-visual biometric recognition system for authenticating humans, using the sequency-mapped real transform for feature extraction. The performance of this new system is compared with previously published results of other systems that only use audio, video, or both. The proposed system demonstrates better performance metrics by utilizing the complementary strengths of both modalities and by employing a new transform that cuts down on computational complexity.

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  • How to Cite

    Panicker, L. S., & Gopikakumari, R. (2025). A novel multi-modal biometric authentication system with enhanced feature extraction using advanced mapped real transform. International Journal of Engineering & Technology, 14(1), 1-6. https://doi.org/10.14419/tn22a349