JOURNAL ARTICLE

Robust Watermarking Algorithm against the Geometric Attacks based on Non-Subsampled Shearlet Transform and Harris-Laplace Detector

Ling ZhouMei-Juan ZuoHao ShiYe ZhangLi‐Hua Gong

Year: 2022 Journal:   Security and Communication Networks Vol: 2022 Pages: 1-14   Publisher: Hindawi Publishing Corporation

Abstract

With the rapid spread of network information, the information maintenance has become the focus of information security on networks. Digital watermarking is one of the effective methods to protect information security, achieve anticounterfeiting traceability, and protect copyright, and it is an important branch of information hiding technology. However, one of the most challenging questions of digital watermarking is how to present strong robustness in geometric attacks. Nowadays, most watermarking algorithms are relatively weak robustness against geometric attacks. A robust watermarking algorithm against geometric attacks based on the non-subsampled shearlet transform and the Harris-Laplace detector is proposed. The host image is decomposed into subbands with different directions by the shearlet transform, and the Harris-Laplace detector is utilized to obtain the feature regions. Then, the nonoverlapping regions with strong robustness are selected to embed watermark by the fuzzy c-means cluster algorithm. The experimental results indicate that the proposed watermarking scheme can well resist geometric attacks.

Keywords:
Digital watermarking Computer science Robustness (evolution) Algorithm Watermark Laplace transform Detector Computer vision Artificial intelligence Image (mathematics) Mathematics

Metrics

8
Cited By
0.99
FWCI (Field Weighted Citation Impact)
36
Refs
0.73
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Steganography and Watermarking Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Chaos-based Image/Signal Encryption
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Digital Media Forensic Detection
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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