Adaptive data hiding for vector quantization images based on overlapping codeword clustering

Authors:
Yen-Shing Tsai;Piyu Tsai
Affiliations:
Department of Computer Science and Information Engineering, National United University, Miaoli 360, Taiwan;Department of Computer Science and Information Engineering, National United University, Miaoli 360, Taiwan
Venue:
Information Sciences: an International Journal
Year:
2011

Citing 12
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Abstract

In this paper, an overlapping codeword clustering based data hiding scheme is presented. In this scheme, a mapping table is designed to determine the overlapping codeword clustering and to indicate the index modification in the secret embedding. The mapping table explores the relationship among the sub-codebook's size, the codeword's order and the embedding secret message to which the codeword overlapping in sub-codebooks with different sizes is permitted. In addition, the secret embedding is also determined according to the mapping table. The experimental results showed that the number of partitioned sub-codebooks was increased significantly. The average hiding capacity was about 30K bits while the average embedding distortion was about 1.2dB. In comparison to similar methods, the proposed scheme provided a larger hiding capacity than others while preserving a similar stego-image quality. Furthermore, the proposed scheme offered a better proportion of hiding compared to image distortion.