Abstract
Most state-of-the-art halftone image data hiding methods aim to preserve good visual quality when embedding messages, while ignoring the statistical security. This paper proposed a halftone steganographic scheme that improves the visual quality and the statistical security of the anti-steganalysis. First, a general distortion measurement for halftone images based on human visual system (HVS) model is proposed. Utilizing the Least-Mean-Square (LMS) method, halftone images can be converted to grayscale images and the objective image quality assessment is applied to evaluate the distortion caused by flipping pixels. Different distortion measurements can be derived from different image quality assessments. Then, to further measure the embedding distortions, we combine these distortion measurements to construct a reassigned distortion measurement based on the controversial pixels prior (CPP) rule. Finally, syndrome-trellis code (STC) is employed to minimize the number of flipping pixels. Experimental results have shown that the proposed steganographic scheme achieves strong statistical security with high capacity and visual quality.
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Acknowledgements
This work is supported by the Key Areas R&D Program of Guangdong (No. 2019B010136002), the National Natural Science Foundation of China (No. U2001202, No. 62072480, No. U1736118), the National Key R&D Program of China (No. 2019QY2202, No. 2019QY(Y)0207), the Key Scientific Research Program of Guangzhou (No. 201804020068).
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Xu, W., Liu, W., Lin, C., Wang, K., Wang, W., Lu, W. (2021). Halftone Image Steganography Based on Reassigned Distortion Measurement. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2021. Lecture Notes in Computer Science(), vol 12737. Springer, Cham. https://doi.org/10.1007/978-3-030-78612-0_30
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