Clustering image noise patterns by embedding and visualization for common source camera detection

We consider the problem of clustering a large set of images based on similarities of their noise patterns. Such clustering is necessary in forensic cases in which detection of common source of images is required, when the cameras are not physically available. We propose a novel method for clustering...

Full description

Saved in:
Bibliographic Details
Published in:Digital investigation 2017-12, Vol.23, p.22-30
Main Authors: Georgievska, Sonja, Bakhshi, Rena, Gavai, Anand, Sclocco, Alessio, van Werkhoven, Ben
Format: Article
Language:English
Subjects:
Clustering
Common image source detection
Digital camera identification
Digital forensics
Photo-response non-uniformity
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We consider the problem of clustering a large set of images based on similarities of their noise patterns. Such clustering is necessary in forensic cases in which detection of common source of images is required, when the cameras are not physically available. We propose a novel method for clustering combining low dimensional embedding, visualization, and classical clustering of the dataset based on the similarity scores. We evaluate our method on the Dresden images database showing that the methodology is highly effective.
ISSN:1742-2876
1873-202X
DOI:10.1016/j.diin.2017.08.005