Title
Performance Analysis of a Block-Neighborhood-Based Self-Recovery Fragile Watermarking Scheme
Abstract
In this paper, we present the performance analysis of a self-recovery fragile watermarking scheme using block-neighbor- hood tamper characterization. This method uses a pseudorandom sequence to generate the nonlinear block-mapping and employs an optimized neighborhood characterization method to detect the tampering. Performance of the proposed method and its resistance to malicious attacks are analyzed. We also investigate three optimization strategies that will further improve the quality of tamper localization and recovery. Simulation results demonstrate that the proposed method allows image recovery with an acceptable visual quality (peak signal-to-noise ratio (PSNR) as 25 dB) up to 60% tampering.
Year
DOI
Venue
2012
10.1109/TIFS.2011.2162950
IEEE Transactions on Information Forensics and Security - Part 2
Keywords
Field
DocType
tampering detection,pseudorandom sequence,image authentication,optimization strategies,nonlinear block-mapping,acceptable visual quality,tamper localization,image watermarking,block-neighborhood tamper characterization,fragile watermarking,tamper recovery,image recovery,tamper detection,block-neighborhood,optimization strategy,block-neighborhood-based self-recovery fragile watermarking,peak signal-to-noise ratio,malicious attacks,block-neighborhood- based self-recovery fragile watermarking scheme,optimized neighborhood characterization method,performance analysis,malicious attack,self-recovery,random sequences,payloads,authentication,watermarking,image restoration,peak signal to noise ratio,feature extraction
Computer vision,Self recovery,Digital watermarking,Nonlinear system,Authentication,Pattern recognition,Computer science,Feature extraction,Artificial intelligence,Image restoration,Image recovery,Payload
Journal
Volume
Issue
ISSN
7
1
1556-6013
Citations 
PageRank 
References 
28
0.95
23
Authors
5
Name
Order
Citations
PageRank
Hongjie He123820.34
Fan Chen213711.05
Heng-Ming Tai323221.77
Ton Kalker41203140.78
Jiashu Zhang5112275.03