Forensic Similarity for Source Camera Model Comparison

In the article "Forensic Similarity for Digital Images", O. Mayer and M. C. Stamm introduce the forensic similarity approach, which aims at determining whether two image patches contain the same forensic traces or not. The proposed method is based on a feed-forward neural network which con...

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Bibliographic Details
Published in:Image processing on line 2022-11, Vol.12, p.480-489
Main Authors: Gardella, Marina, Musé, Pablo
Format: Article
Language:English
Subjects:
Computer Science
Computer Vision and Pattern Recognition
Online Access:Get full text
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Summary:In the article "Forensic Similarity for Digital Images", O. Mayer and M. C. Stamm introduce the forensic similarity approach, which aims at determining whether two image patches contain the same forensic traces or not. The proposed method is based on a feed-forward neural network which consists of two modules: a feature extraction module using a pair of CNNs in a siamese configuration, and a three-layer neural network that maps the extracted features into a similarity score. In this article, we explore the use of the forensic similarity score for source camera model comparison, as one of the possible applications of such an approach suggested by Mayer and Stamm. Source Code The source code and documentation for this algorithm are available from the web page of this article 1. Usage instructions are included in the README.txt file of the archive. The original implementation of the method is available here 2. This is an MLBriefs article, the source code has not been reviewed!
ISSN:2105-1232
2105-1232
DOI:10.5201/ipol.2022.424