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Quality metric‐based fitness function for robust watermarking optimisation with Bees algorithm
Author(s) -
Abdelhakim Assem M.,
Saleh Hassan I.,
Nassar Amin M.
Publication year - 2016
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2015.0379
Subject(s) - robustness (evolution) , digital watermarking , discrete cosine transform , watermark , embedding , fitness function , peak signal to noise ratio , computer science , algorithm , mathematics , metric (unit) , artificial intelligence , mathematical optimization , image (mathematics) , engineering , genetic algorithm , operations management , biochemistry , chemistry , gene
The design of a robust watermarking technique has been always suffering from the conflict between the watermark robustness and the quality of the watermarked image. In this study, the embedding strength parameters for per‐block image watermarking in the discrete cosine transform (DCT) domain are optimised. A fitness function is proposed to best suit the optimisation problem. The optimum solution is selected based on the quality and the robustness achieved using that solution. For a given image block, the peak‐signal‐to‐noise ratio (PSNR) is used as a quality metric to measure the imperceptibility for the watermarked block. However, the robustness cannot be measured for a single watermark bit using traditional metrics. The proposed method uses the PSNR quality metric to indicate the degree of robustness. Hence, optimum embedding in terms of quality and robustness can be achieved. To demonstrate the effectiveness of the proposed approach, a recent watermarking technique is modified, and then used as the embedding method to be optimised. The Bees algorithm is selected as the optimisation method and the proposed fitness function is applied. Experimental results show that the proposed method provides enhanced imperceptibility and robustness under different attacks.

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