Title: Data hiding using lifting scheme and genetic algorithm

Authors: Geeta Kasana; Kulbir Singh; Satvinder Singh Bhatia

Addresses: Department of Computer Science and Engineering, Thapar University, Patiala, 147004, India ' Department of Electronics and Communication Engineering, Thapar University, Patiala, 147004, India ' School of Mathematics, Thapar University, Patiala, 147004, India

Abstract: In this paper, data hiding algorithm by using lifting scheme and genetic algorithm (GA) has been proposed. Arnold transform has been used to scramble the secret image to secure the extraction of secret image. Lifting scheme is applied on the cover image to get the wavelet subbands. In this algorithm, scrambled secret image is embedded into significant wavelet coefficients of subbands of cover image. Scaling factor (SF) parameter is used in embedding and extracting process of the proposed algorithm and GA is used to optimise this parameter. This optimisation is used to maximise the value of peak signal to noise ratio (PSNR) of composite image and similarity index modulation (SIM) of extracted secret image. Experimental results reveal that proposed algorithm provides high embedding capacity and better quality of composite images than the existing data hiding techniques. To show the effectiveness of the proposed algorithm, statistical tests have been performed to show that the imperceptibility is maintained.

Keywords: lifting scheme; Arnold transform; peak signal noise ratio; genetic algorithm; similarity index modulation; SIM; integer wavelet transform; IWT; scaling factor; SF.

DOI: 10.1504/IJICS.2017.087561

International Journal of Information and Computer Security, 2017 Vol.9 No.4, pp.271 - 287

Accepted: 23 May 2016
Published online: 18 Oct 2017 *

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