20 May 2019 Detecting double compression for JPEG images of low quality factor
Huiling Yuan, Bo Ou, Huawei Tian
Author Affiliations +
Abstract
Double JPEG compression is often used to conceal some illegal operations on the source image. Since there exist some traces when an image undergoes double JPEG compression, the detection of double JPEG compression can be used as a tool of digital forensics. In the past decade, researchers have focused on detecting double compression with the same quality factor (QF) but cannot provide reliable results when the QF is approximately below 70. To remedy this, we propose to analyze the low-frequency components and the error image and extract two types of features to improve the detection accuracy. Since the high-frequency components are easily lost in the JPEG compression, the low-frequency components are utilized to extract the reliable features. With this in mind, our method first analyzes the low-frequency discrete cosine transform coefficients and the lost information. Then, the features are extracted to characterize the difference between the two sequential compressions. Finally, the feature set is fed to a support vector machine for classification. Experimental results on two standard image databases verify that our method could improve the detection accuracy of the low QF double compressed JPEG images with the same QF. The average classification accuracy of the different QFs (the range of QF is usually set from 70 to 20) was obtained as 87.75%.
© 2019 SPIE and IS&T 1017-9909/2019/$25.00 © 2019 SPIE and IS&T
Huiling Yuan, Bo Ou, and Huawei Tian "Detecting double compression for JPEG images of low quality factor," Journal of Electronic Imaging 28(3), 033011 (20 May 2019). https://doi.org/10.1117/1.JEI.28.3.033011
Received: 10 November 2018; Accepted: 29 April 2019; Published: 20 May 2019
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Image compression

Image processing

Quantization

Feature extraction

Forensic science

Databases

Error analysis

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