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Source Camera Identification for Heavily JPEG Compressed Low Resolution Still Images *
Author(s) -
Alles Erwin J.,
Geradts Zeno J. M. H.,
Veenman Cor J.
Publication year - 2009
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/j.1556-4029.2009.01029.x
Subject(s) - computer vision , jpeg , identification (biology) , artificial intelligence , computer science , low resolution , computer graphics (images) , high resolution , pattern recognition (psychology) , remote sensing , data compression , geology , botany , biology
In this research, we examined whether fixed pattern noise or more specifically Photo Response Non‐Uniformity (PRNU) can be used to identify the source camera of heavily JPEG compressed digital photographs of resolution 640 × 480 pixels. We extracted PRNU patterns from both reference and questioned images using a two‐dimensional Gaussian filter and compared these patterns by calculating the correlation coefficient between them. Both the closed and open‐set problems were addressed, leading the problems in the closed set to high accuracies for 83% for single images and 100% for around 20 simultaneously identified questioned images. The correct source camera was chosen from a set of 38 cameras of four different types. For the open‐set problem, decision levels were obtained for several numbers of simultaneously identified questioned images. The corresponding false rejection rates were unsatisfactory for single images but improved for simultaneous identification of multiple images.