A New Dataset for Source Identification of High Dynamic Range Images
Digital source identification is one of the most important problems in the field of multimedia forensics. While Standard Dynamic Range (SDR) images are commonly analyzed, High Dynamic Range (HDR) images are a less common research subject, which leaves space for further analysis. In this paper, we pr...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-11-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/18/11/3801 |
| _version_ | 1798002520907317248 |
|---|---|
| author | Omar Al Shaya Pengpeng Yang Rongrong Ni Yao Zhao Alessandro Piva |
| author_facet | Omar Al Shaya Pengpeng Yang Rongrong Ni Yao Zhao Alessandro Piva |
| author_sort | Omar Al Shaya |
| collection | DOAJ |
| description | Digital source identification is one of the most important problems in the field of multimedia forensics. While Standard Dynamic Range (SDR) images are commonly analyzed, High Dynamic Range (HDR) images are a less common research subject, which leaves space for further analysis. In this paper, we present a novel database of HDR and SDR images captured in different conditions, including various capturing motions, scenes and devices. As a possible application of this dataset, the performance of the well-known reference pattern noise-based source identification algorithm was tested on both kinds of images. Results have shown difficulties in source identification conducted on HDR images, due to their complexity and wider dynamic range. It is concluded that capturing conditions and devices themselves can have an impact on source identification, thus leaving space for more research in this field. |
| first_indexed | 2024-04-11T11:53:25Z |
| format | Article |
| id | doaj.art-c1c72418db8a4672a1985cd20434a06e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T11:53:25Z |
| publishDate | 2018-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c1c72418db8a4672a1985cd20434a06e2022-12-22T04:25:14ZengMDPI AGSensors1424-82202018-11-011811380110.3390/s18113801s18113801A New Dataset for Source Identification of High Dynamic Range ImagesOmar Al Shaya0Pengpeng Yang1Rongrong Ni2Yao Zhao3Alessandro Piva4Department of Information Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, ItalyBeijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, ChinaBeijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, ChinaBeijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, ChinaDepartment of Information Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, ItalyDigital source identification is one of the most important problems in the field of multimedia forensics. While Standard Dynamic Range (SDR) images are commonly analyzed, High Dynamic Range (HDR) images are a less common research subject, which leaves space for further analysis. In this paper, we present a novel database of HDR and SDR images captured in different conditions, including various capturing motions, scenes and devices. As a possible application of this dataset, the performance of the well-known reference pattern noise-based source identification algorithm was tested on both kinds of images. Results have shown difficulties in source identification conducted on HDR images, due to their complexity and wider dynamic range. It is concluded that capturing conditions and devices themselves can have an impact on source identification, thus leaving space for more research in this field.https://www.mdpi.com/1424-8220/18/11/3801datasetmultimedia forensicsimage forensicsHDRsource identification |
| spellingShingle | Omar Al Shaya Pengpeng Yang Rongrong Ni Yao Zhao Alessandro Piva A New Dataset for Source Identification of High Dynamic Range Images Sensors dataset multimedia forensics image forensics HDR source identification |
| title | A New Dataset for Source Identification of High Dynamic Range Images |
| title_full | A New Dataset for Source Identification of High Dynamic Range Images |
| title_fullStr | A New Dataset for Source Identification of High Dynamic Range Images |
| title_full_unstemmed | A New Dataset for Source Identification of High Dynamic Range Images |
| title_short | A New Dataset for Source Identification of High Dynamic Range Images |
| title_sort | new dataset for source identification of high dynamic range images |
| topic | dataset multimedia forensics image forensics HDR source identification |
| url | https://www.mdpi.com/1424-8220/18/11/3801 |
| work_keys_str_mv | AT omaralshaya anewdatasetforsourceidentificationofhighdynamicrangeimages AT pengpengyang anewdatasetforsourceidentificationofhighdynamicrangeimages AT rongrongni anewdatasetforsourceidentificationofhighdynamicrangeimages AT yaozhao anewdatasetforsourceidentificationofhighdynamicrangeimages AT alessandropiva anewdatasetforsourceidentificationofhighdynamicrangeimages AT omaralshaya newdatasetforsourceidentificationofhighdynamicrangeimages AT pengpengyang newdatasetforsourceidentificationofhighdynamicrangeimages AT rongrongni newdatasetforsourceidentificationofhighdynamicrangeimages AT yaozhao newdatasetforsourceidentificationofhighdynamicrangeimages AT alessandropiva newdatasetforsourceidentificationofhighdynamicrangeimages |