In this paper, a simple yet reliable algorithm to detect the presence of nonaligned double JPEG compression (NA-JPEG) in compressed images is proposed. The method evaluates a single feature based on the integer periodicity of the blockwise discrete cosine transform (DCT) coefficients when the DCT is computed according to the grid of the previous JPEG compression. Even if the proposed feature is computed relying only on DC coefficient statistics, a simple threshold detector can classify NA-JPEG images with improved accuracy with respect to existing methods and on smaller image sizes, without resorting to a properly trained classifier. Moreover, the proposed scheme is able to accurately estimate the grid shift and the quantization step of the DC coefficient of the primary JPEG compression, allowing one to perform a more detailed analysis of possibly forged images.
Detection of Nonaligned Double JPEG Compression Based on Integer Periodicity Maps / Bianchi, Tiziano; A., Piva. - In: IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY. - ISSN 1556-6013. - 7:2(2012), pp. 842-848. [10.1109/TIFS.2011.2170836]
Detection of Nonaligned Double JPEG Compression Based on Integer Periodicity Maps
BIANCHI, TIZIANO;
2012
Abstract
In this paper, a simple yet reliable algorithm to detect the presence of nonaligned double JPEG compression (NA-JPEG) in compressed images is proposed. The method evaluates a single feature based on the integer periodicity of the blockwise discrete cosine transform (DCT) coefficients when the DCT is computed according to the grid of the previous JPEG compression. Even if the proposed feature is computed relying only on DC coefficient statistics, a simple threshold detector can classify NA-JPEG images with improved accuracy with respect to existing methods and on smaller image sizes, without resorting to a properly trained classifier. Moreover, the proposed scheme is able to accurately estimate the grid shift and the quantization step of the DC coefficient of the primary JPEG compression, allowing one to perform a more detailed analysis of possibly forged images.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2505891
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