Abstract
Embedding large quantities of data in VQ (Vector Quantization) images is a thorny problem, since the hiding schemes usually have to change the index values of the VQ images, which might cause serious image distortion. As a result, many currently existing methods can only afford to support a small embedding capacity. In this article, we shall propose a new method that uses the genetic clustering technique on the codebook to obtain better clusters so that the replacement distortion of indices can be reduced. Then, we apply multi-way search to hide the secret data. Experimental results show that our new method outperforms existing schemes on both image quality and embedding capacity.
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© 2005 Springer-Verlag Berlin Heidelberg
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Chang, CC., Lin, CY., Wang, YZ. (2005). VQ Image Steganographic Method with High Embedding Capacity Using Multi-way Search Approach. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553939_148
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DOI: https://doi.org/10.1007/11553939_148
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28896-1
Online ISBN: 978-3-540-31990-0
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