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Coverless Video Steganography Based on Frame Sequence Perceptual Distance Mapping

Runze Li1, Jiaohua Qin1,*, Yun Tan1, Neal N. Xiong2

1 College of Computer Science and Information Technology, Central South University of Forestry & Technology, Changsha, 410004, China
2 Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, 74464, OK, USA

* Corresponding Author: Jiaohua Qin. Email: email

Computers, Materials & Continua 2022, 73(1), 1571-1583. https://doi.org/10.32604/cmc.2022.029378

Abstract

Most existing coverless video steganography algorithms use a particular video frame for information hiding. These methods do not reflect the unique sequential features of video carriers that are different from image and have poor robustness. We propose a coverless video steganography method based on frame sequence perceptual distance mapping. In this method, we introduce Learned Perceptual Image Patch Similarity (LPIPS) to quantify the similarity between consecutive video frames to obtain the sequential features of the video. Then we establish the relationship map between features and the hash sequence for information hiding. In addition, the MongoDB database is used to store the mapping relationship and speed up the index matching speed in the information hiding process. Experimental results show that the proposed method exhibits outstanding robustness under various noise attacks. Compared with the existing methods, the robustness to Gaussian noise and speckle noise is improved by more than 40%, and the algorithm has better practicability and feasibility.

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Cite This Article

APA Style
Li, R., Qin, J., Tan, Y., Xiong, N.N. (2022). Coverless video steganography based on frame sequence perceptual distance mapping. Computers, Materials & Continua, 73(1), 1571-1583. https://doi.org/10.32604/cmc.2022.029378
Vancouver Style
Li R, Qin J, Tan Y, Xiong NN. Coverless video steganography based on frame sequence perceptual distance mapping. Comput Mater Contin. 2022;73(1):1571-1583 https://doi.org/10.32604/cmc.2022.029378
IEEE Style
R. Li, J. Qin, Y. Tan, and N.N. Xiong "Coverless Video Steganography Based on Frame Sequence Perceptual Distance Mapping," Comput. Mater. Contin., vol. 73, no. 1, pp. 1571-1583. 2022. https://doi.org/10.32604/cmc.2022.029378



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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