Double JPEG Compression Detection Based on Noise-Free DCT Coefficients Mixture Histogram Model

• Published in: Symmetry (Basel) Vol. 11; no. 9; p. 1119
• Main Authors: Zhu, Nan, Shen, Junge, Niu, Xiaotong
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2019
• Subjects: Authenticity; Coefficients; Conditional probability; DCT coefficient; Digital imaging; Digital signatures; Discrete cosine transform; double compression; double quantization; Editing; Histograms; Image compression; image forensics; Image manipulation; JPEG encoders-decoders; Localization; Mathematical models; Methods; Noise; Principal components analysis; quantization noise; Rounding
• ISSN: 2073-8994; 2073-8994
• DOI: 10.3390/sym11091119

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.