FloreView: An Image and Video Dataset for Forensic Analysis
Linking a digital image or video to its originating device, or checking the content integrity still represent challenging forensic tasks. Even though several technologies based on metadata, file format, and sensor noise have been developed to address these problems, current methods are frequently ma...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10271281/ |
| _version_ | 1797660815145304064 |
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| author | Daniele Baracchi Dasara Shullani Massimo Iuliani Alessandro Piva |
| author_facet | Daniele Baracchi Dasara Shullani Massimo Iuliani Alessandro Piva |
| author_sort | Daniele Baracchi |
| collection | DOAJ |
| description | Linking a digital image or video to its originating device, or checking the content integrity still represent challenging forensic tasks. Even though several technologies based on metadata, file format, and sensor noise have been developed to address these problems, current methods are frequently made obsolete by new customized acquisition pipelines implemented by manufacturers. Therefore, to assess the performance of the available tools and push the research activity, researchers continuously need new datasets containing contents captured with recent technologies. In this paper, we present a new image and video dataset for forensic analysis. Data, acquired by the most recent acquisition devices, were collected under strictly controlled procedures designed to limit the bias induced by differences in the acquisition process between different devices. The dataset includes over 9000 media contents captured by 46 smartphones of 11 major brands. For each device, we collected at least 100 unique natural images, 30 unique natural videos, 30 flat images, and 4 flat videos. Great care has been taken in collecting data that can be used for multiple forensic tasks; moreover, images and videos have been carefully organized so that FloreView could be used by the community immediately and effortlessly. Finally, two case studies related to image source identification and video brand identification have been performed, using state-of-the-art methods, to show how the proposed dataset can be effectively used for forensic tasks. |
| first_indexed | 2024-03-11T18:36:17Z |
| format | Article |
| id | doaj.art-d99131a74f5c43758f081322ef6a6df0 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T18:36:17Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d99131a74f5c43758f081322ef6a6df02023-10-12T23:01:29ZengIEEEIEEE Access2169-35362023-01-011110926710928210.1109/ACCESS.2023.332199110271281FloreView: An Image and Video Dataset for Forensic AnalysisDaniele Baracchi0https://orcid.org/0000-0002-7364-1955Dasara Shullani1https://orcid.org/0000-0003-2753-366XMassimo Iuliani2https://orcid.org/0000-0002-5501-4667Alessandro Piva3https://orcid.org/0000-0002-3047-0519Department of Information Engineering, University of Florence, Florence, ItalyDepartment of Information Engineering, University of Florence, Florence, ItalyDepartment of Information Engineering, University of Florence, Florence, ItalyDepartment of Information Engineering, University of Florence, Florence, ItalyLinking a digital image or video to its originating device, or checking the content integrity still represent challenging forensic tasks. Even though several technologies based on metadata, file format, and sensor noise have been developed to address these problems, current methods are frequently made obsolete by new customized acquisition pipelines implemented by manufacturers. Therefore, to assess the performance of the available tools and push the research activity, researchers continuously need new datasets containing contents captured with recent technologies. In this paper, we present a new image and video dataset for forensic analysis. Data, acquired by the most recent acquisition devices, were collected under strictly controlled procedures designed to limit the bias induced by differences in the acquisition process between different devices. The dataset includes over 9000 media contents captured by 46 smartphones of 11 major brands. For each device, we collected at least 100 unique natural images, 30 unique natural videos, 30 flat images, and 4 flat videos. Great care has been taken in collecting data that can be used for multiple forensic tasks; moreover, images and videos have been carefully organized so that FloreView could be used by the community immediately and effortlessly. Finally, two case studies related to image source identification and video brand identification have been performed, using state-of-the-art methods, to show how the proposed dataset can be effectively used for forensic tasks.https://ieeexplore.ieee.org/document/10271281/Datasetsimage analysisimage forensicsvideo forensicssource identification |
| spellingShingle | Daniele Baracchi Dasara Shullani Massimo Iuliani Alessandro Piva FloreView: An Image and Video Dataset for Forensic Analysis IEEE Access Datasets image analysis image forensics video forensics source identification |
| title | FloreView: An Image and Video Dataset for Forensic Analysis |
| title_full | FloreView: An Image and Video Dataset for Forensic Analysis |
| title_fullStr | FloreView: An Image and Video Dataset for Forensic Analysis |
| title_full_unstemmed | FloreView: An Image and Video Dataset for Forensic Analysis |
| title_short | FloreView: An Image and Video Dataset for Forensic Analysis |
| title_sort | floreview an image and video dataset for forensic analysis |
| topic | Datasets image analysis image forensics video forensics source identification |
| url | https://ieeexplore.ieee.org/document/10271281/ |
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