A new multiplicative watermark detector in the contourlet domain using t Location-Scale distribution. (May 2018)

• Record Type: Journal Article
• Authors: Etemad, Sadegh; Amirmazlaghani, Maryam
• Is Part Of: Pattern recognition. Volume 77(2018:May)
• Page Start: 99
• Page End: 112
• Publication Date: 2018-05
• Subjects: Statistical modeling -- Contourlet transform -- t Location-Scale distribution -- Multiplicative watermark -- Likelihood ratio test; Pattern perception -- Periodicals; Perception des structures -- Périodiques; Patroonherkenning; 006.4
• DOI: 10.1016/j.patcog.2017.12.006
• Languages: English
• ISSNs: 0031-3203

Abstract

Highlights: Modeling contourlet coefficients using t Location-Scale distribution. Study adaptation between t Location-Scale distribution and contourlet coefficients. Designing a contourlet domain multiplicative watermark detector using LRT. Deriving ROC of the watermark detector theoretically and analyzing its performance. Abstract: Digital watermarking is used to protect copyright information by embedding hidden data in digital media. In this study, a multiplicative watermarking scheme is proposed in the contourlet domain. Overall, selection of proper models is of great importance, as watermark detection processes can be replicated as decision rules. Accordingly, in this study, contourlet coefficients were modeled based on t-location scale distribution. Based on the Kolmogorov–Smirnov test, t Location-Scale distribution showed high efficiency in modeling the coefficients. We used the likelihood ratio decision rule and t-location scale distribution to design an optimal multiplicative watermark detector. Then, we derive the receiver operating characteristics (ROC) analytically. The detector showed higher efficiency than other watermarking schemes in the literature, based on the experimental results, and its robustness against different attacks was verified.