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Robust Blind Video Watermarking Based on Ring Tensor and BCH Coding

delete2024-12-15
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PRE
AI
J
Jiayan Wang
赵敬 cover
赵敬 (Jing Zhao)
L
Li Li
Z
Zichi Wang
H
Hanzhou Wu
D
Deyang Wu *
DOI:10.1109/JIOT.2024.3453960delete
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Abstract

Abstract

En 中文
Video Internet of Things (IoT) is widely used in the fields of safe city, smart transportation, and logistics warehousing, which facilitates the acquisition of important environmental and semantic information. However, the tampering of unauthorized video data may seriously violate user privacy and even harm society. Although the existing video watermarking technology provides an effective solution for copyright protection, it still faces challenges to achieve robust copyright authentication in the complex IoT environment. In this article, a robust blind video watermarking based on ring Tensor and Bose-Chaudhuri-Hocquenghem (BCH) coding is proposed. First, ring sub-bands of different sizes are constructed in the spatial domain of the video, and the ring sub-bands of consecutive video frames are combined into a ring tensor for copyright watermark embedding. Second, to balance the imperceptibility and robustness of the copyright watermark, an adaptive BCH coding scheme is developed, which uses the modified differential entropy to calculate the video complexity and automatically selects the appropriate watermark coding parameters. Finally, a quaternary synchronization watermark embedding strategy is designed to solve the time synchronization destruction caused by video frame rate conversion. A synchronization ring is constructed within each video frame using the strong correlation between adjacent frames. When the video is subjected to temporal synchronization attacks, the synchronization watermark is extracted from the synchronization ring to restore the synchronization of the copyright watermark. Extensive experimental results demonstrate that the proposed scheme can effectively resist common video processing while exhibiting excellent robustness against video attacks in complex Internet environments.
Keywords:
Watermarking
Tensors
Encoding
Robustness
Frequency-domain analysis
Feature extraction
Synchronization
Blind watermarking
Bose-Chaudhuri-Hocquenghem (BCH) coding
double watermarking
ring tensor
video watermarking

Journal

IEEE Internet of Things Journal cover
IEEE Internet of Things Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W

Organization

Y
Yanshan University
Scholars:
1.7W
Papers: 1.1W
Citations: 1.3W
S
shanghai university
Scholars:
3.9W
Papers: 2.7W
Citations: 52