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Source Camera Identification Issues: Forensic Features Selection and Robustness
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Author(s): Yongjian Hu (South China University of Technology, China, and University of Warwick, UK), Chang-Tsun Li (University of Warwick, UK), Changhui Zhou (South China University of Technology, China)and Xufeng Lin (South China University of Technology, China)
Copyright: 2011
Volume: 3
Issue: 4
Pages: 15
Source title:
International Journal of Digital Crime and Forensics (IJDCF)
Editor(s)-in-Chief: Feng Liu (Chinese Academy of Sciences, China)
DOI: 10.4018/jdcf.2011100101
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Abstract
Statistical image features play an important role in forensic identification. Current source camera identification schemes select image features mainly based on classification accuracy and computational efficiency. For forensic investigation purposes; however, these selection criteria are not enough. Consider most real-world photos may have undergone common image processing due to various reasons, source camera classifiers must have the capability to deal with those processed photos. In this work, the authors first build a sample camera classifier using a combination of popular image features, and then reveal its deficiency. Based on the experiments, suggestions for the design of robust camera classifiers are given.
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