Abstract
With the wide use of various image altering tools, digital image manipulation becomes very convenient and easy, which makes the detection of image originality and authenticity significant. Among various image tampering detection tools, double JPEG image compression detector, which is not sensitive to specific image tampering operation, has received large attention. In this paper, we propose an improved double JPEG compression detection method based on noise-free DCT (Discrete Cosine Transform) coefficients mixture histogram model. Specifically, we first extract the block-wise DCT coefficients histogram and eliminate the quantization noise which introduced by rounding and truncation operations. Then, for each DCT frequency, a posterior probability can be obtained by solving the DCT coefficients mixture histogram with a simplified model. Finally, the probabilities from all the DCT frequencies are accumulated to give the posterior probability of a DCT block being authentic or tampered. Extensive experimental results in both quantitative and qualitative terms prove the superiority of our proposed method when compared with the state-of-the-art methods.
Highlights
With the rapid growth of image acquisition devices and the popularity of social networks, digital images have become an important form of information exchange, which leads to the fact that digital images are being utilized more often to support important decisions in daily life
We focus on the aligned double JPEG compression
We propose an improved double JPEG compression detection method based on noise-free DCT coefficients mixture histogram model
Summary
With the rapid growth of image acquisition devices and the popularity of social networks, digital images have become an important form of information exchange, which leads to the fact that digital images are being utilized more often to support important decisions in daily life. This is especially true in the applications related to criminal investigation, law enforcement, military, and scientific research. Blind digital image forensic technologies, which aim to verify the originality and authenticity of digital images without any prior knowledge, have become a research hotspot
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