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Recursive Visual Cryptography Scheme with PRWP and Additional Basis Matrix

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Evolution in Computational Intelligence

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 267))

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Abstract

Recursive visual cryptography scheme (RVCS) is a high-security image secret sharing scheme in which the shares are recursively encoded into sub-shares at numerous levels. Here we presented a new scheme for RVCS with a perfect reconstruction of white pixels (PRWP) and an additional basis matrix (ABM) which boosts contrast. The method has been illustrated on the basis of investigational examinations. We made an evaluation between the conventional schemes and the proposed scheme through investigational analysis. The results revealed that our scheme improves the visual quality and ensures security and reliability.

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Authors and Affiliations

  1. Department of Information Technology, Kannur University, Kannur, 670 567, Kerala, India

    T. E. Jisha

  2. Department of Computer Science, Mary Matha Arts and Science College, Kannur University, Mananthavady, Wayanad, 670 645, Kerala, India

    Thomas Monoth

Authors
  1. T. E. Jisha
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Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  2. College of Computing, Michigan Technological University, Michigan, MI, USA

    Jinshan Tang

  3. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, India

    Suresh Chandra Satapathy

  4. Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia

    Peter Peer

  5. Department of Computer Science and Engineering, National Institute of Technology (NIT) Mizoram, Aizawl, India

    Ranjita Das

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Jisha, T.E., Monoth, T. (2022). Recursive Visual Cryptography Scheme with PRWP and Additional Basis Matrix. In: Bhateja, V., Tang, J., Satapathy, S.C., Peer, P., Das, R. (eds) Evolution in Computational Intelligence. Smart Innovation, Systems and Technologies, vol 267. Springer, Singapore. https://doi.org/10.1007/978-981-16-6616-2_17

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