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Optimized interesting region identification for video steganography using multi-objective cost function

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Abstract

This paper presents an optimal data hiding in videos using optimization based on multi-objective constraints such as, the energy of wavelet, intensity, edge details, and energy of Local Binary Patterns (LBP). The Fractional-Cat swarm optimization (Fractional-CSO) is modelled with the inclusion of fractional calculus in Cat swarm optimization (CSO). Initially, an input video is selected from which frames are generated. The key frames are extracted from those frames using the Contourlet Transform (CT) and Structural Similarity Index (SSIM). Regions are formed on the selected key frames with the help of grid lines. Finally, the optimal region for embedding is interpreted using the proposed optimization algorithm along with multi-objective cost functions to embed the secret message. The secret data is hidden in the optimal region using the Lifting Wavelet Transform (LWT). Then the embedded video is subsequently sent across the network to its intended recipient. The experimental analysis is done using two videos which reveal the effectiveness of the proposed video steganography. The comparative analysis based on the MSE (Mean-Square Error), Peak Signal to Noise Ratio (PSNR) and correlation measure reveals the effectiveness of the method. With MSE of 0.0001, maximal PSNR of 82.273 dB and correlation of 0.9529 respectively shows increase in security of the data with a better quality embedded image. For noise free image, the correlation acquired using the proposed video steganography is 0.9934.

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Authors and Affiliations

  1. Department of Computer Science, Nesamony Memorial Christian College affiliated to Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu, 627012, India

    Meenu Suresh

  2. Department of PG Computer Science, Nesamony Memorial Christian College affiliated to Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu, 627012, India

    I. Shatheesh Sam

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Suresh, M., Sam, I.S. Optimized interesting region identification for video steganography using multi-objective cost function. Multimed Tools Appl 82, 31373–31396 (2023). https://doi.org/10.1007/s11042-023-14821-3

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