Title: An ant colony optimisation for data hiding in greyscale images

Authors: Sidi Mohamed Douiri; Souad Elbernoussi

Addresses: Faculty of Sciences, Laboratory of Mathematic Informatics and Applications, University Mohammed V-Agdal, B.P. 1014, Rabat, Morocco ' Faculty of Sciences, Laboratory of Mathematic Informatics and Applications, University Mohammed V-Agdal, B.P. 1014, Rabat, Morocco

Abstract: The least significant bit (LSB) embedding method is one of the most frequently used techniques for information hiding, but it can degrade image quality significantly, particularly when a large number of bits are replaced. In this paper, a new approach to improve the embedding capacity and provide an imperceptible visual quality are proposed, using an effective ant colony optimisation algorithm to locate the optimal positions of the pixels in the over image to hide a data. Experimental results reveal that the stego-image is visually identical from the original over-image and the proposed approach can hide a large size of informations with reasonable computation time. Compare these results with previously achieved work also shows a significant improvement.

Keywords: data hiding; ant colony optimisation; ACO; least significant bit; LSB substitution; metaheuristics; swarm intelligence; greyscale images; image quality; embedding capacity; visual quality.

DOI: 10.1504/IJOR.2017.083177

International Journal of Operational Research, 2017 Vol.29 No.1, pp.101 - 114

Received: 24 Dec 2013
Accepted: 09 Sep 2014
Published online: 22 Mar 2017 *

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