Open Access

ARTICLE

Multi-Feature Fragile Image Watermarking Algorithm for Tampering Blind-Detection and Content Self-Recovery

Qiuling Wu^1,*, Hao Li¹, Mingjian Li¹, Ming Wang²

1 Cyber Security Academy, Jinling Institute of Technology, Nanjing, 211169, China
2 Xinghua Branch, State Grid Jiangsu Electric Power Co., Ltd., Xinghua, 225700, China

* Corresponding Author: Qiuling Wu. Email:

Computers, Materials & Continua 2026, 86(1), 1-20. https://doi.org/10.32604/cmc.2025.068220

Received 23 May 2025; Accepted 06 August 2025; Issue published 10 November 2025

Abstract

Digital watermarking technology plays an important role in detecting malicious tampering and protecting image copyright. However, in practical applications, this technology faces various problems such as severe image distortion, inaccurate localization of the tampered regions, and difficulty in recovering content. Given these shortcomings, a fragile image watermarking algorithm for tampering blind-detection and content self-recovery is proposed. The multi-feature watermarking authentication code (AC) is constructed using texture feature of local binary patterns (LBP), direct coefficient of discrete cosine transform (DCT) and contrast feature of gray level co-occurrence matrix (GLCM) for detecting the tampered region, and the recovery code (RC) is designed according to the average grayscale value of pixels in image blocks for recovering the tampered content. Optimal pixel adjustment process (OPAP) and least significant bit (LSB) algorithms are used to embed the recovery code and authentication code into the image in a staggered manner. When detecting the integrity of the image, the authentication code comparison method and threshold judgment method are used to perform two rounds of tampering detection on the image and blindly recover the tampered content. Experimental results show that this algorithm has good transparency, strong and blind detection, and self-recovery performance against four types of malicious attacks and some conventional signal processing operations. When resisting copy-paste, text addition, cropping and vector quantization under the tampering rate (TR) 10%, the average tampering detection rate is up to 94.09%, and the peak signal-to-noise ratio (PSNR) of the watermarked image and the recovered image are both greater than 41.47 and 40.31 dB, which demonstrates its excellent advantages compared with other related algorithms in recent years.

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Keywords

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