Abstract
Although researchers have noticed that HVS is very important component in designing data hiding algorithms, most of existing spatial data hiding techniques do not truly use the model of HVS to improve the performance. In this paper, we propose a spatial data hiding using pixel-based JND (Just-Noticeable Distortion) model to modify the difference image between host image and predictive image to hide the data. Experimental results show that the stego-image is visually indistinguishable from the original cover-image and has better quality for stego image, and more important, the proposed method considers the characteristic of HVS truly. Compared with existing similar algorithm, the proposed quality-progressive hiding means that one can hide all secret data up to the capacity of the algorithm without changing any parameters. However, existing similar algorithm must change some parameters to hide data according to the length of data in order to achieve better performance.
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References
Petitcolas, F.A.P., Anderson, R.J., Kuhn, M.G.: Information Hiding – a Survey. Proceedings of the IEEE Special issue on Protection of Multimedia Content 87(7), 1062–1078 (1999)
Westfeld, A., Pfitzmann, A.: Attacks on Steganographic System. In: Pfitzmann, A. (ed.) IH 1999. LNCS, vol. 1768, pp. 61–76. Springer, Heidelberg (2000)
Chan, C.K., Cheng, L.M.: Hiding Data in Images by Simple LSB Substitution. Pattern Recognition 37(3), 469–474 (2004)
Liu, S.H., Yao, H.X., Gao, W., et al.: Minimizing the Distortion Spatial Data Hiding Based on Equivalence Class. In: ICIC (1), pp. 667–678 (2007)
Trivedi, S.L., Chandramouli, R.: Active Steganalysis of Sequential Steganography. In: Proceeding of SPIE-IS&T Electronic Imaging, Security and Watermarking of Multimedia Contents V, vol. 5020, pp. 123–130. SPIE, San Jose (2003)
Lie, W.N., Chang, L.C.: Data Diding in Images with Adaptive Numbers of Least Signficant Bits based on the Human Visual System. In: Proceedings of international conference of Image Processing (IEEE ICIP), pp. 286–290 (1999)
Wu, D.C., Tsai, W.H.: A Steganographic Method for Images by Pixel-value Differencing. Pattern Recognition Letters 24(9-10), 1613–1626 (2003)
Chang, C.C., Tseng, H.W.: A Steganographic Method for Digital Images Using Side Match. Pattern Recognition Letters 25, 1431–1437 (2004)
Lee, L.S., Tsai, W.H.: Data Hiding in Grayscale Images by Dynamic Programming based on a Human Visual Model. Pattern Recognition 42(7), 1604–1611 (2009)
Jung, K.H., Yoo, K.Y.: Data Hiding Method Using Image Interpolation. Computer Standards & Interfaces 31(2), 465–470 (2009)
Yu, Y.H., Chang, C.C., Hu, Y.C.: Hiding Secret Data in Images Via Predictive Coding. Pattern Recognition 38(5), 691–705 (2005)
Yang, X.K., Lin, W.S., Lu, Z.K., et al.: Motion-compensated Residue Pre-processing in Video Coding Based on Just-noticeable-distortion Profile. IEEE Trans. Circuits and Systems for Video Technology 15(6), 742–750 (2005)
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Liu, S., Jiang, F., Yao, H., Zhao, D. (2010). An Image Data Hiding Method Using Pixel-Based JND Model. In: Huang, DS., McGinnity, M., Heutte, L., Zhang, XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14831-6_42
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DOI: https://doi.org/10.1007/978-3-642-14831-6_42
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