Abstract
In this paper, a new and efficient image hiding scheme is proposed. Different from the existing methods, the secret data is embedded into the prediction errors produced by the neural network nonlinear predictor, and the non-uniform quantization method is used to embed secret data. The proposed method can achieve higher embedding payload while keeping smaller distortion, and experimental results are given to show the advantage of this scheme.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Lie, W.N., Chang, L.C.: Data Hiding in Images with Adaptive Numbers of Least Significant Bits Based on the Human Visual System. In: Proc. Int. Conf. Image Processing, pp. 286–290. IEEE Computer Society, Kobe Japan (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)
Yu, Y.H., Chang, C.C., Hu, Y.C.: Hiding Secret Data in Images via Predictive Coding. Pattern Recognition 38(5), 691–705 (2005)
Memon, N., Wu, X.L.: Recent Developments in Context-based Predictive Techniques for Lossless Image Compression. Computer Journal 40(2-3), 127–136 (1997)
Dianat, S.A., Nasrabadi, N.M., Venkataraman, S.: A Non-linear Predictor for Differential Pulse-code Encoder(DPCM) Using Artificial Neural Network. In: Proc. Int. Conf. Acoustics, Speech, and Signal Processing, pp. 2793–2796. IEEE Computer Society, Toronto (1991)
Hagan, M.T., Demuth, H.B., Beale, M.H.: Neural Network Design. PWS Publishing Company, Boston (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, G., Wang, J., Lian, S., Dai, Y., Wang, Z. (2006). Data Hiding in Neural Network Prediction Errors. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_40
Download citation
DOI: https://doi.org/10.1007/11760191_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34482-7
Online ISBN: 978-3-540-34483-4
eBook Packages: Computer ScienceComputer Science (R0)
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.