A New Hybrid DCT and Contourlet Transform Based JPEG Image Steganalysis Technique

Authors:
Zohaib Khan;Atif Bin Mansoor
Affiliations:
College of Aeronautical Engineering, National University of Sciences & Technology, Pakistan;College of Aeronautical Engineering, National University of Sciences & Technology, Pakistan
Venue:
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Year:
2009

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Abstract

In this paper, a universal steganalysis scheme for JPEG images based upon hybrid transform features is presented. We first analyzed two different transform domains (Discrete Cosine Transform and Discrete Contourlet Transform) separately, to extract features for steganalysis. Then a combination of these two feature sets is constructed and employed for steganalysis. A Fisher Linear Discriminant classifier is trained on features from both clean and steganographic images using all three feature sets and subsequently used for classification. Experiments performed on images embedded with two variants of F5 and Model based steganographic techniques reveal the effectiveness of proposed steganalysis approach by demonstrating improved detection for hybrid features.