{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T07:24:34Z","timestamp":1772954674838,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,1,13]],"date-time":"2021-01-13T00:00:00Z","timestamp":1610496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>The Photo Response Non-Uniformity pattern (PRNU-pattern) can be used to identify the source of images or to indicate whether images have been made with the same camera. This pattern is also recognized as the \u201cfingerprint\u201d of a camera since it is a highly characteristic feature. However, this pattern, identically to a real fingerprint, is sensitive to many different influences, e.g., the influence of camera settings. In this study, several previously investigated factors were noted, after which three were selected for further investigation. The computation and comparison methods are evaluated under variation of the following factors: resolution, length of the video and compression. For all three studies, images were taken with a single iPhone 6. It was found that a higher resolution ensures a more reliable comparison, and that the length of a (reference) video should always be as high as possible to gain a better PRNU-pattern. It also became clear that compression (i.e., in this study the compression that Snapchat uses) has a negative effect on the correlation value. Therefore, it was found that many different factors play a part when comparing videos. Due to the large amount of controllable and non-controllable factors that influence the PRNU-pattern, it is of great importance that further research is carried out to gain clarity on the individual influences that factors exert.<\/jats:p>","DOI":"10.3390\/jimaging7010008","type":"journal-article","created":{"date-parts":[[2021,1,13]],"date-time":"2021-01-13T11:52:32Z","timestamp":1610538752000},"page":"8","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Factors that Influence PRNU-Based Camera-Identification via Videos"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1579-9890","authenticated-orcid":false,"given":"Lars","family":"de Roos","sequence":"first","affiliation":[{"name":"Faculty of Technology, Amsterdam University of Applied Sciences, 1097 DZ Amsterdam, The Netherlands"},{"name":"Department of Digital and Biometric Traces, Netherlands Forensic Institute, 2467 GB The Hague, The Netherlands"}]},{"given":"Zeno","family":"Geradts","sequence":"additional","affiliation":[{"name":"Department of Digital and Biometric Traces, Netherlands Forensic Institute, 2467 GB The Hague, The Netherlands"},{"name":"Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,13]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Forensic Camera Classification: Verification of Sensor Pattern Noise Approach","volume":"11","author":"Khanna","year":"2009","journal-title":"Forensic Sci. 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