Evidence map›Paper›PMID 40399347›Full record

ArticleScientific reports2025

A robust fragile watermarking approach for image tampering detection and restoration utilizing hybrid transforms.

S Prasanth Vaidya, Rajesh N V P S Kandala, P V S S R Chandra Mouli, Hatim G Zaini, Amar Jaffar, Prabhu Paramasivam, Sherif S M Ghoneim

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

S Prasanth VaidyaDepartment of Computer Science, BVRIT HYDERABAD College of Engineering for Women, Hyderabad, Telangana, India.
Rajesh N V P S KandalaSchool of Electronics Engineering, VIT-AP University, Vijayawada, Andhra Pradesh, India. kandala.rajesh2014@gmail.com.
P V S S R Chandra MouliDepartment of Computer Science, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India.
Hatim G ZainiComputer Engineering Department, College of Computer and Information Technology, Taif University, 21944, Taif, Saudi Arabia.
Amar JaffarComputer and Network Engineering Department, College of Computing, Umm Al-Qura University, Mecca, Saudi Arabia.
Prabhu ParamasivamDepartment of Mechanical Engineering, Mattu University, Metu, Ethiopia. pkmaghilan@gmail.com.
Sherif S M GhoneimDepartment of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a novel fragile watermarking technique to detect and restore image tampering, enhancing security in digital image transmission. The proposed method integrates Schur decomposition and discrete wavelet transform (DWT) for watermark embedding, ensuring robustness against attacks compared to existing methods. Schur decomposition provides numerical stability in matrix factorization, while DWT enhances resilience through multi-resolution analysis. A semi-blind extraction algorithm, relying only on a secret key, enables active tampering detection without requiring the original image. Upon detection of distortions, the proposed recovery mechanism restores the tampered regions of the image. The effectiveness of the proposed scheme is validated through structural similarity, peak signal-to-noise ratio, and normalized cross-correlation metrics, demonstrating superior performance compared to existing methods. This approach is applicable to secure medical imaging, forensic investigations, and copyright protection, ensuring image integrity in real-world scenarios.

Indexed as

Digital watermarkingDiscrete wavelet transform (DWT)Image recoveryImage tamper detection

Identifiers

PMID40399347
PMCPMC12095512

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.