Genetic algorithms for optimality of data hiding in digital images

Authors:
Santi P. Maity;Malay K. Kundu
Affiliations:
Bengal Engineering and Science University, Department of Information Technology, Shibpur, 711103, Howrah, India;Indian Statistical Institute, Center for Soft Computing Research and Machine Intelligence Unit, 203 B.T. Road, 700 108, Kolkata, India
Venue:
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Bio-Inspired Information Hiding; Guest editors: Jeng-Shyang Pan, Ajith Abraham
Year:
2008

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Abstract

This paper investigates the scope of usage of Genetic Algorithms (GA) for data hiding in digital images. The tool has been explored in this topic of research to achieve an optimal solution in multidimensional nonlinear problem of conflicting nature that exists among imperceptibility, robustness, security and payload capacity. Two spatial domain data hiding methods are proposed where GA is used separately for (i) improvement in detection and (ii) optimal imperceptibility of hidden data in digital images respectively. In the first method, GA is used to achieve a set of parameter values (used as Key) to represent optimally the derived watermark in the form of approximate difference signal used for embedding. In the second method, GA is used for finding out values of parameters, namely reference amplitude (A) and modulation index (μ) both with linear and non linear transformation functions, for achieving the optimal data imperceptibility. Results on robustness for both the methods against linear, non linear filtering, noise addition, and lossy compression as well as statistical invisibility of the hidden data are reported here for some benchmark images.