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• W3043385148 startingPage "300983" @default.
• W3043385148 abstract "Digital forensics is a topic that has attracted many attention. One of the most common tasks in digital forensics is imaging sensor identification. It may be understood as recognizing devices origin based on subject that this device produced. Therefore, areas that match digital forensics include among others: digital camera, flatbed scanner or printer identification. In this paper we survey methods and algorithms for digital camera identification. The goal of digital camera identification algorithm is to identify and distinct camera's sensor based on produced images. This topic is especially popular in forensics' community since last years. The paper discusses two concepts for camera identification: individual source camera identification (ISCI) and source camera model identification (SCMI). The ISCI aims to distinguish a certain camera among cameras of both the same and the different camera models, while the SCMI distinguishes a certain camera model among others but cannot distinguish a certain camera among the same camera models. We investigate methods dealing with these concepts that include: camera's photo response non uniformity (PRNU) identification, statistical methods, analysis of camera's optical defects, machine learning and deep models which include convolutional neural networks. We also provide a description of popular image datasets that can be used for camera identification algorithms evaluation." @default.
• W3043385148 created "2020-07-23" @default.
• W3043385148 creator A5056200449 @default.
• W3043385148 date "2020-09-01" @default.
• W3043385148 modified "2023-10-11" @default.
• W3043385148 title "A survey on digital camera identification methods" @default.
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• W3043385148 doi "https://doi.org/10.1016/j.fsidi.2020.300983" @default.
• W3043385148 hasPublicationYear "2020" @default.
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