JOURNAL ARTICLE
Form follows function: Applying photographic content analysis to forensic firearm identification.
Published In: Journal of Forensic Sciences, 2023, v. 68, n. 6. P. 2153 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Chaikovsky, Alan; Pasternak, Zohar; Finkelstein, Nir; Chattah, Netta Lev Tov; Silchenko, Alexander; Levy, Ophir; Cohen, Amit 3 of 3
Abstract
Drawing forensic conclusions from an image or a video is known as "photographic content analysis." It involves the analysis of an image, as well as objects, actions, and events depicted in images or video. In recent years, photographic depictions of objects suspected as illegal firearms have substantially increased, appearing on CCTV surveillance footage, captured by mobile phones and shared on social media. However, the law in Israel states that a person can be charged with illegally possessing a firearm only if it can be proven that the object is capable of shooting with lethal bullet energy. This becomes more challenging in cases where the firearm was not physically seized, and the evidence exclusively consists of images and video. In this study, photographic content analysis was applied to images and video where objects suspected as commercial or improvised firearms had been depicted. An image and event sequence reconstruction video databases of both firearms and replicas were created in order to better define firearm‐specific functional morphological features. We demonstrate that it is possible to classify an object as a firearm by analyzing the functional, and not only the esthetic, morphology in images and video. It is also shown that event sequence reconstruction in video may be used to infer that an object suspected as a firearm has the capacity to shoot by confirming the occurrence of a shooting act or shooting process. Thus, photographic content analysis may be used to forensically establish that an object depicted in an image or a video is a firearm by ruling out other known scenarios, and without physically seizing it. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Forensic Sciences. 2023/11, Vol. 68, Issue 6, p2153
- Document Type:Article
- Subject Area:Science
- Publication Date:2023
- ISSN:0022-1198
- DOI:10.1111/1556-4029.15363
- Accession Number:173182025
- Copyright Statement:Copyright of Journal of Forensic Sciences is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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