Image forensics using generalised Benford's Law for improving image authentication detection rates in semifragile watermarking

Xi Zhao, Anthony T.S. Ho, Yun Q. Shi

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1-20
Number of pages20
JournalInternational Journal of Digital Crime and Forensics
Volume2
Issue number2
DOIs
StatePublished - Apr 2010

All Science Journal Classification (ASJC) codes

  • Software

Keywords

  • DCT
  • Generalised Benford's Law
  • Image authentication
  • Image enhancement
  • JPEG compression
  • Semi-fragile watermarking

Fingerprint Dive into the research topics of 'Image forensics using generalised Benford's Law for improving image authentication detection rates in semifragile watermarking'. Together they form a unique fingerprint.

Cite this