Title
Spotting The Difference: Context Retrieval And Analysis For Improved Forgery Detection And Localization
Abstract
As image tampering becomes ever more sophisticated and commonplace, the need for image forensics algorithms that can accurately and quickly detect forgeries grows. In this paper, we revisit the ideas of image querying and retrieval to provide clues to better localize forgeries. We propose a method to perform large-scale image forensics on the order of one million images using the help of an image search algorithm and database to gather contextual clues as to where tampering may have taken place. In this vein, we introduce five new strongly invariant image comparison methods and test their effectiveness under heavy noise, rotation, and color space changes. Lastly, we show the effectiveness of these methods compared to passive image forensics using Nimble [1], a new, state-of-the-art dataset from the National Institute of Standards and Technology (NIST).
Year
DOI
Venue
2017
10.1109/icip.2017.8297049
2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
Keywords
DocType
Volume
image forensics, forgery detection, splicing detection, context-aware digital forensics, tampering heat maps
Conference
abs/1705.00604
ISSN
Citations 
PageRank 
1522-4880
3
0.37
References 
Authors
17
9
Name
Order
Citations
PageRank
Joel Brogan1142.93
Paolo Bestagini226132.01
Aparna Bharati3304.56
Allan da Silva Pinto41306.99
daniel medeiros moreira581.78
Bowyer, K.6388.39
Patrick J. Flynn730820.13
Anderson Rocha891369.11
Walter J. Scheirer977352.81