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Score-based Likelihood Ratios for Camera Device Identification

Conference/Workshop:
IS&T International Symposium on Electronic Imaging, Media Watermarking, Security, and Forensics
Published: 2020
Primary Author: Stephanie Reinders
Secondary Authors: Li Lin, Wenhao Chen, Yong Guan, Jennifer Newman
Research Area: Digital

Many areas of forensics are moving away from the notion of classifying evidence simply as a match or non-match. Instead, some use score-based likelihood ratios (SLR) to quantify the similarity between two pieces of evidence, such as a fingerprint obtained from a crime scene and a fingerprint obtained from a suspect. We apply trace-anchored score-based likelihood ratios to the camera device identification problem. We use photo-response non-uniformity (PRNU) as a camera fingerprint and one minus the normalized correlation as a similarity score. We calculate trace-anchored SLRs for 10,000 images from seven camera devices from the BOSSbase image dataset. We include a comparison between our results the universal detector method.

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