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Image Forensics Using Generalised Benford's Law for Improving Image Authentication Detection Rates in Semi-Fragile Watermarking

Image Forensics Using Generalised Benford's Law for Improving Image Authentication Detection Rates in Semi-Fragile Watermarking

Xi Zhao, Anthony T. S. Ho, Yun Q. Shi
Copyright: © 2010 |Volume: 2 |Issue: 2 |Pages: 20
ISSN: 1941-6210|EISSN: 1941-6229|EISBN13: 9781609604042|DOI: 10.4018/jdcf.2010040101
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MLA

Zhao, Xi, et al. "Image Forensics Using Generalised Benford's Law for Improving Image Authentication Detection Rates in Semi-Fragile Watermarking." IJDCF vol.2, no.2 2010: pp.1-20. http://doi.org/10.4018/jdcf.2010040101

APA

Zhao, X., Ho, A. T., & Shi, Y. Q. (2010). Image Forensics Using Generalised Benford's Law for Improving Image Authentication Detection Rates in Semi-Fragile Watermarking. International Journal of Digital Crime and Forensics (IJDCF), 2(2), 1-20. http://doi.org/10.4018/jdcf.2010040101

Chicago

Zhao, Xi, Anthony T. S. Ho, and Yun Q. Shi. "Image Forensics Using Generalised Benford's Law for Improving Image Authentication Detection Rates in Semi-Fragile Watermarking," International Journal of Digital Crime and Forensics (IJDCF) 2, no.2: 1-20. http://doi.org/10.4018/jdcf.2010040101

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Abstract

In the past few years, semi-fragile watermarking has become increasingly important to verify the content of images and localise the tampered areas, while tolerating some non-malicious manipulations. In the literature, the majority of semi-fragile algorithms have applied a predetermined threshold to tolerate errors caused by JPEG compression. However, this predetermined threshold is typically fixed and cannot be easily adapted to different amounts of errors caused by unknown JPEG compression at different quality factors (QFs). In this paper, the authors analyse the relationship between QF and threshold, and propose the use of generalised Benford’s Law as an image forensics technique for semi-fragile watermarking. The results show an overall average QF correct detection rate of approximately 99%, when 5%, 20% and 30% of the pixels are subjected to image content tampering and compression using different QFs (ranging from 95 to 65). In addition, the authors applied different image enhancement techniques to these test images. The proposed image forensics method can adaptively adjust the threshold for images based on the estimated QF, improving accuracy rates in authenticating and localising the tampered regions for semi-fragile watermarking.

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