Abstract
Non-intrusive digital image forensics (NIDIF) is a novel approach to authenticate the trustworthiness of digital images. It works by exploring varieties of intrinsic characteristics involved in the digital imaging, editing, storing processes as discriminative features to reveal the subtle traces left by a malicious fraudster. The NIDIF for the lossy JPEG image format is of special importance for its pervasive application. In this paper, we propose an NIDIF framework for the JPEG images. The framework involves two complementary identification methods for exposing shifted double JPEG (SD-JPEG) compression artifacts, including an improved ICA-based method and a First Digits Histogram based method. They are designed to treat the detectable conditions and a few special undetectable conditions separately. Detailed theoretical justifications are provided to reveal the relationship between the detectability of the artifacts and some intrinsic statistical characteristics of natural image signal. The extensive experimental results have shown the effectiveness of the proposed methods. Furthermore, some case studies are also given to demonstrate how to reveal certain types of image manipulations, such as cropping, splicing, or both, with our framework.
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Qu, Z., Luo, W. & Huang, J. A framework for identifying shifted double JPEG compression artifacts with application to non-intrusive digital image forensics. Sci. China Inf. Sci. 57, 1–18 (2014). https://doi.org/10.1007/s11432-013-5046-8
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DOI: https://doi.org/10.1007/s11432-013-5046-8