Steganalysis based on image quality metrics

Ismail Avcibaş, Nasir Memon, Bülent Sankur

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, we present techniques for steganalysis of images that have been potentially subjected to a watermarking algorithm. We show that watermarking schemes leave statistical evidence or structure that can be exploited for detection with the aid of proper selection of image features and multivariate regression analysis. We use some image quality metrics as the feature set to distinguish between watermarked and unwatermarked images and furthermore distinguish between different watermarking techniques. To identify specific quality measures that provide the best discriminative power, we use analysis of variance (ANOVA) techniques. Multivariate regression analysis is then used on the selected quality metrics to build an optimal classifier using a set of test images and their blurred versions. Simulation results with a specific feature set and some well-known and publicly available watermarking techniques indicate that our approach is able to accurately distinguish with high accuracy between images marked by different watermarking techniques.

Original languageEnglish (US)
Title of host publication2001 IEEE Fourth Workshop on Multimedia Signal Processing
EditorsJ.-L. Dugelay, K. Rose, J.-L. Dugelay, K. Rose
Number of pages6
StatePublished - 2001
Event2001 IEEE fourth Workshop on Multimedia Signal Processing - Cannes, France
Duration: Oct 3 2001Oct 5 2001

Publication series

Name2001 IEEE Fourth Workshop on Multimedia Signal Processing


Other2001 IEEE fourth Workshop on Multimedia Signal Processing

ASJC Scopus subject areas

  • General Engineering


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