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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 11, 2024.
Abstract: In order to more effectively hide and extract image information, a deep neural network-based algorithm and computer-aided image information hiding method is proposed. The hardware design of the system includes the selection of the main control chip, the design of the parallel processing structure, and the design of the Ethernet communication circuit; Software design includes an image information hiding module, an image information extraction module, and a carrier image processing module. The operation of the image information processing system based on the reversible information hiding algorithm is realized through the system hardware and software design. The experimental results show that the carrier image processing degree of the design system is much higher than that of the traditional system, and the maximum value can reach 91%, indicating that the carrier image processing performance of the design system is better. The scheme proposed in this paper can improve the security of secret information while ensuring the quality of dense image. Follow-up studies will continue to explore the combination of adversarial learning and various traditional embedding algorithms to further improve the concealment of graph-hiding algorithms.
Zhe Zhang, “Image Information Hiding Processing Based on Deep Neural Network Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 15(11), 2024. http://dx.doi.org/10.14569/IJACSA.2024.01511132
@article{Zhang2024,
title = {Image Information Hiding Processing Based on Deep Neural Network Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01511132},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01511132},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {11},
author = {Zhe Zhang}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.