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A Novel Secure Personal Authentication System with Finger in Face Watermarking Mechanism

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Advances in Soft Computing and Machine Learning in Image Processing

Part of the book series: Studies in Computational Intelligence ((SCI,volume 730))

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Abstract

Facial and Finger authentication plays a pivotal role for proving personal verification in any organization, industry, enterprise, etc. In the previous works, authentication systems are developed by using the password, pin number, digital signature, etc., as a single source of identification. But all these systems can be subjected to spoofing attack. In this paper, a novel authentication system is proposed with image-in-image Fast Hadmard Transform (FHT) watermarking and authentication with Singular Value Decomposition (SVD). The proposed system is strong enough from attacks as the authentication is being done using face and finger traits. The proposed work is useful for reducing the size of the database, identification and authentication for bank systems, crime investigations, organizational attendance systems, and for knowing student attendance system, unauthorized copying, etc.

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Authors and Affiliations

  1. Department of CSE, S.R.K.R Engineering College, W.G. District, Bhimavaram, 534 204, Andhra Pradesh, India

    Chinta Someswara Rao, K. V. S. Murthy, R. Shiva Shankar & V. Mnssvkr Gupta

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  1. Chinta Someswara Rao
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  2. K. V. S. Murthy
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  3. R. Shiva Shankar
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  4. V. Mnssvkr Gupta
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Correspondence to Chinta Someswara Rao .

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Editors and Affiliations

  1. Faculty of Computers and Information, Information Technology Department, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. CUCEI, Departamento de Ciencias Computacionales, Universidad de Guadalajara, Guadalajara, Mexico

    Diego Alberto Oliva

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Rao, C.S., Murthy, K.V.S., Shankar, R.S., Gupta, V.M. (2018). A Novel Secure Personal Authentication System with Finger in Face Watermarking Mechanism. In: Hassanien, A., Oliva, D. (eds) Advances in Soft Computing and Machine Learning in Image Processing. Studies in Computational Intelligence, vol 730. Springer, Cham. https://doi.org/10.1007/978-3-319-63754-9_15

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  • DOI: https://doi.org/10.1007/978-3-319-63754-9_15

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