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| Main Authors: | , , |
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| Format: | Preprint |
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2024
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| Online Access: | https://arxiv.org/abs/2407.00543 |
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| _version_ | 1866912081021763584 |
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| author | Martin, Abby Maxion, Roy Newman, Jennifer |
| author_facet | Martin, Abby Maxion, Roy Newman, Jennifer |
| contents | Photo response non-uniformity (PRNU) is a technology that can match a digital photograph to the camera that took it. Due to its use in forensic investigations and use by forensic experts in court, it is important that error rates for this technology are reliable for a wide range of evidence image types. In particular, images with off-nominal exposures are not uncommon. This paper presents a preliminary investigation of the impact that images with different exposure types - too dark or too light - have on error rates for PRNU source camera identification. We construct a new dataset comprised of 8400 carefully collected images ranging from under-exposed (too dark) to nominally exposed to over-exposed (too bright). We first establish baseline error rates using only nominally exposed images, resulting in a true-positive rate of 100% and a true-negative rate of 99.92%. When off-nominal images are tested, we find striking results: the true-negative rate for under-exposed images is 99.46% (a false-positive rate of roughly one in two hundred, typically unacceptable in a forensic context), and for over-exposed images the true-positive rate falls to 82.90%. Our results highlight the importance of continued study of error rates for the PRNU source camera identification to assure adherence to the high standards set for admissibility of forensic evidence in court. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_00543 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Forensic Camera Identification: Effects of Off-Nominal Exposures Martin, Abby Maxion, Roy Newman, Jennifer Image and Video Processing Photo response non-uniformity (PRNU) is a technology that can match a digital photograph to the camera that took it. Due to its use in forensic investigations and use by forensic experts in court, it is important that error rates for this technology are reliable for a wide range of evidence image types. In particular, images with off-nominal exposures are not uncommon. This paper presents a preliminary investigation of the impact that images with different exposure types - too dark or too light - have on error rates for PRNU source camera identification. We construct a new dataset comprised of 8400 carefully collected images ranging from under-exposed (too dark) to nominally exposed to over-exposed (too bright). We first establish baseline error rates using only nominally exposed images, resulting in a true-positive rate of 100% and a true-negative rate of 99.92%. When off-nominal images are tested, we find striking results: the true-negative rate for under-exposed images is 99.46% (a false-positive rate of roughly one in two hundred, typically unacceptable in a forensic context), and for over-exposed images the true-positive rate falls to 82.90%. Our results highlight the importance of continued study of error rates for the PRNU source camera identification to assure adherence to the high standards set for admissibility of forensic evidence in court. |
| title | Forensic Camera Identification: Effects of Off-Nominal Exposures |
| topic | Image and Video Processing |
| url | https://arxiv.org/abs/2407.00543 |