Faculty Publications
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Publications by NITK Faculty
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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.Item Enhanced optical flow-based full reference video quality assessment algorithm(Springer, 2022) Gujjunoori, S.; Oruganti, M.; Pais, A.R.Full reference video quality assessment based on optical flow is emerging. Human Visual System (HVS) based video quality assessment algorithms are playing an important role in effectively assessing the distortions in video sequences. There exist very few video quality assessment algorithms which consider spatio-temporal distortions effectively. To address the above issues, we present an enhanced optical flow based full reference video quality algorithm which considers the orientation feature of the optical flow while computing the temporal distortions as opposed to the use of feature, minimum eigenvalue as in the state of the art. Further, it presents an interquartile range based comparative weighted closeness (INT-CWC) measure which aimed to measure the comparative dispersion of video quality scores of any two video quality assessment algorithms with DMOS scores. Here INT-CWC measure is a novel attempt. The performance of proposed scheme is evaluated using the LIVE dataset and scheme is shown to be competitive with, and even out-perform, existing video quality assessment algorithms. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.