Open AccessA reversible information hiding algorithm in AMBTC domain based on human vision system
Author(s) -
Tao Zhang,
Jiantao Ding,
Zhewen Tian
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1982/1/012071
Subject(s) - information hiding , computer science , artificial intelligence , computer vision , block (permutation group theory) , human visual system model , histogram , robustness (evolution) , algorithm , pattern recognition (psychology) , image (mathematics) , mathematics , biochemistry , chemistry , geometry , gene
Compression is a common processing method of digital image, and the compression of carrier image usually affects the performance of hidden information. Therefore, it is necessary to research on the preprocessing method to improve some performance of hidden information in the compressed domain. Aiming at the problem of tampering attack on compressed domain image and the security of secret information preprocessing in the previous information hiding algorithms, we propose a reversible information hiding algorithm in AMBTC domain based on human vision system. Firstly, RGB color image is converted to YCbCr image, AMBTC coding is used to generate high and low average value sequence in brightness component. Secondly, the secret information is compressed by run length coding and scrambled. Thirdly, the histogram shift technique is used to embed the information into the mean sequence and generate the reserved information at the same time. Fourth, the color component is divided into normal block and absolute smooth fast, the specific position of the bit plane of the normal block is deleted, and the reserved information is embedded. The experimental results show that, compared with other algorithms, the proposed algorithm has better invisibility and robustness, and after a certain attack, the extracted secret information still has high recognizability.