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Blind image—variant based authentication method

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Abstract

There is a plethora of image authentication techniques in the literature. Almost all of these methods use either a form of watermarking or data hiding techniques to embed data directly in the original image or its decomposed sub-bands. Recently, new multiple watermarking methods have emerged to tackle more robust forgery challenges where a single watermark fails or insufficient. Most of these methods are directed towards medical images for obvious reasons. This paper presents a new precise blind image-variant authentication method. This method initiates a new direction for research on image authentication as it does not embed any sort of data in the original image or its decomposed sub-band(s) but rather produces an image-variant via manipulating some statistics of the original image. These variations represent two sequences which were infused in two QR-codes that enabled the variation process. We tested this method against image processing attacks including JPEG compression, resizing, and Gaussian-noise using images from several databases including the USC – SIPI, McGill Calibrated Color Image, DICOM medical image. Also, we compared this method performance with results from seven 7 published methods and found that our method scored higher performance results for robustness and imperceptibility and it regenerated the variation secret sequences with 100% accuracy in each case. Furthermore, this method capacity is large enough to prevent data-overflow.

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Authors and Affiliations

  1. ECE Department, Concordia University, 1455 De Maisonneuve Blvd., Montreal, QC, H3G 1M8, Canada

    Saif alZahir

  2. Computer Science Department, UNBC, Prince George, BC, Canada

    Wahedul Islam

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  1. Saif alZahir
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  2. Wahedul Islam
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Correspondence to Saif alZahir.

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alZahir, S., Islam, W. Blind image—variant based authentication method. Multimed Tools Appl 83, 51899–51923 (2024). https://doi.org/10.1007/s11042-023-17547-4

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  • DOI: https://doi.org/10.1007/s11042-023-17547-4

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