Paper Info
Title
Image alignment based perceptual image hash for content authentication
Abstract
Perceptual image hash is an emerging technology that is closely related to many applications such as image content authentication, image forging detection, image similarity detection, and image retrieval. In this work, we propose an image alignment based perceptual image hash method, and a hash-based image forging detection and tampering localization method. In the proposed method, we introduce an image alignment process to provide a framework for image hash method to tolerate a wide range of geometric distortions. The image hash is generated by utilizing hybrid perceptual features that are extracted from global and local Zernike moments combining with DCT-based statistical features of the image. The proposed method can detect various image forging and compromised image regions. Furthermore, it has broad-spectrum robustness, including tolerating content-preserving manipulations and geometric distortion-resilient. Compared with state-of-the-art schemes, the proposed method provides satisfactory comprehensive performances in content-based image forging detection and tampering localization.
Year
DOI
Venue
2020
10.1016/j.image.2019.115642
Signal Processing: Image Communication
Keywords
Field
DocType
Image alignment,Perceptual image hash,Geometric distortion-resilient,Image forging detection,Image tampering localization
Image alignment,Computer vision,Authentication,Computer science,Discrete cosine transform,Robustness (computer science),Zernike polynomials,Forging,Artificial intelligence,Hash function,Perception
Journal
Volume
ISSN
Citations 
80
0923-5965
2
PageRank 
References 
Authors
0.37
0
5
Name
Order
Citations
PageRank
Xiaofeng Wang1949.88
Xiaorui Zhou220.37
Qian Zhang320.37
Bingchao Xu420.37
J. Xue554257.57