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Open AccessArticle

A New Dataset for Source Identification of High Dynamic Range Images

by Omar Al Shaya 1,2, Pengpeng Yang 3,4, Rongrong Ni 3,4,*, Yao Zhao 3,4 and Alessandro Piva 1,5,*
Department of Information Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, Italy
Department of Electronic Media, Saudi Electronic University, Abi Bakr As Sadiq Rd, Riyadh 11673, Saudi Arabia
Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China
Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China
FORLAB, Multimedia Forensics Laboratory, PIN Scrl, Piazza G. Ciardi, 25, 59100 Prato, Italy
Authors to whom correspondence should be addressed.
Sensors 2018, 18(11), 3801;
Received: 14 September 2018 / Revised: 29 October 2018 / Accepted: 2 November 2018 / Published: 6 November 2018
(This article belongs to the Special Issue Camera Identification on Mobile Devices)
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. View Full-Text
Keywords: dataset; multimedia forensics; image forensics; HDR; source identification dataset; multimedia forensics; image forensics; HDR; source identification
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Shaya, O.A.; Yang, P.; Ni, R.; Zhao, Y.; Piva, A. A New Dataset for Source Identification of High Dynamic Range Images. Sensors 2018, 18, 3801.

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