Faculty Publications

Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736

Publications by NITK Faculty

Browse

Author: search.filters.author.Mhala, N.C.Subject: search.filters.subject.Visual secret sharing schemes

Search Results

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    Randomised visual secret sharing scheme for grey-scale and colour images
    (Institution of Engineering and Technology journals@theiet.org, 2018) Mhala, N.C.; Jamal, R.; Pais, A.R.
    Randomised visual secret sharing is an encryption technique that utilises block-based progressive visual secret sharing and discrete cosine transform (DCT) based reversible data embedding technique to recover a secret image. The recovery method is based on progressive visual secret sharing, which recovers the secret image block by block. The existing block based schemes achieve the highest contrast level of 50% for noise-like and meaningful shares. The proposed scheme achieves a contrast level of 70-90% for noise-like and 70-80% for meaningful shares. The enhancement of contrast is achieved by embedding additional information in the shares using DCT-based reversible data embedding technique. Experimental results showed that the proposed scheme restores the secret image with better visual quality in terms of human visual system based parameters. © The Institution of Engineering and Technology 2017.
  • No Thumbnail Available
    Item
    Verifiable XOR-based visual secret sharing scheme for hyperspectral images
    (SPIE, 2021) Srujana, O.S.; Mhala, N.C.; Pais, A.R.
    Hyperspectral images (HSIs) are the spectral images that provide spatial and spectral information. Unlike multispectral images, these images consist of 100 to 200 bands, which provide a large amount of data to identify minute details of the scene with the help of the spectral signatures. This information is valuable and should be secured while transmitting the HSI over the network. Visual cryptography is a well-known cryptographic method for securing images. It helps in securely transmitting images among n users. It converts visual data into unreadable shares that are transmitted and, stacking these shares together will reveal the image. Many visual secret sharing (VSS) schemes have been proposed in the past decade, which made it easier to hide the visual information from unauthorized users. We have proposed a verifiable XOR-based VSS method for the secure transmission of HSIs. We have introduced a preprocessing step for the image with a band selection technique, which reduces the size of the image and eliminates redundancy. It also includes the detection of the tampered shares. Embedding a verifiable bit in each pixel is performed to test the integrity of the shares. We have assessed the visual quality of the recovered image using quantitative measuring parameters. We also compared them with existing VSS methods. The proposed method recovers the HSI with a self-similarity index of 95% to 99%. The proposed method's experimental results show that the HSI is restored with better visual quality. © 2021 Society of Photo-Optical Instrumentation Engineers (SPIE).
  • No Thumbnail Available
    Item
    A secure visual secret sharing (VSS) scheme with CNN-based image enhancement for underwater images
    (Springer Science and Business Media Deutschland GmbH, 2021) Mhala, N.C.; Pais, A.R.
    Nowadays, underwater images are being used to identify various important resources like objects, minerals, and valuable metals. Due to the wide availability of the Internet, we can transmit underwater images over a network. As underwater images contain important information, there is a need to transmit them securely over a network. Visual secret sharing (VSS) scheme is a cryptographic technique, which is used to transmit visual information over insecure networks. Recently proposed randomized VSS (RVSS) scheme recovers secret image (SI) with a self-similarity index (SSIM) of 60–80%. But, RVSS is suitable for general images, whereas underwater images are more complex than general images. In this paper, we propose a VSS scheme using super-resolution for sharing underwater images. Additionally, we have removed blocking artifacts from the reconstructed SI using convolution neural network (CNN)-based architecture. The proposed CNN-based architecture uses a residue image as a cue to improve the visual quality of the SI. The experimental results show that the proposed VSS scheme can reconstruct SI with almost 86–99% SSIM. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.