Aligned and Non-Aligned Double JPEG Detection Using Convolutional Neural Networks

Due to the wide diffusion of JPEG coding standard, the image forensic community has devoted significant attention to the development of double JPEG (DJPEG) compression detectors through the years. The ability of detecting whether an image has been compressed twice provides paramount information toward image authenticity assessment. Given the trend recently gained by convolutional neural networks (CNN) in many computer vision tasks, in this paper we propose to use CNNs for aligned and non-aligned double JPEG compression detection. In particular, we explore the capability of CNNs to capture DJPEG artifacts directly from images. Results show that the proposed CNN-based detectors achieve good performance even with small size images (i.e., 64x64), outperforming state-of-the-art solutions, especially in the non-aligned case. Besides, good results are also achieved in the commonly-recognized challenging case in which the first quality factor is larger than the second one.Comment: Submitted to Journal of Visual Communication and Image Representation (first submission: March 20, 2017; second submission: August 2, 2017

New Framework for Code-Mapping-based Reversible Data Hiding in JPEG Images

Code mapping (CM) is an efficient technique of reversible data hiding (RDH) in JPEG images, which embeds data by constructing the mapping relationship between used codes and unused codes in JPEG bitstream. In this paper, we present a new framework to design the CM-based RDH method. Firstly, to suppress the file size expansion and improve the applicability, a new code mapping strategy is proposed. Based on the proposed strategy, the mapped codes are redefined by customizing a new Huffman table thoroughly rather than selected from the unused codes in the original Huffman table. Afterwards, the key issue of designing the CM-based RDH method, i.e., constructing the code mapping, is converted into solving a combinatorial optimization problem. As a realization, a novel CM-based RDH method is introduced by employing the genetic algorithm (GA). Experimental results show that the efficacy of the proposed method with high embedding capacity and no signal distortion while suppressing file size expansion

Robusna procedura za umetanje vodenog žiga u sliku zasnovana na Hermitovoj projekcijskoj metodi

A procedure for combined image watermarking and compression, based on the Hermite projection method is proposed. The Hermite coefficients obtained by using the Hermite expansion are used for watermark embedding. The image can be efficiently reconstructed by using a set of Hermite coefficients that is quite smaller than the number of original ones. Hence, the watermark embedding is actually done in the compressed domain, while maintaining still high image quality (measured by high PSNR). The efficiency of the proposed procedure is proven experimentally, showing high robustness even for very strong standard attacks. Moreover, the method is robust not only to the standard attacks, but to the geometrical attacks, as well. The proposed approach can be suitable for different copyright and ownership protection purposes, especially in real-applications that require image compression, such as multimedia and Internet applications, remote sensing and satellite imaging.U radu je predložena procedura za umetanje vodenog žiga u sliku i kompresiju slike zasnovana na Hermitovoj projekcijskoj metodi. Odgovarajući koeficijenti, dobiveni kao rezultat primjene razvoja slike u red Hermitovih funkcija, korišteni su za umetanje vodenog žiga watermark). S obzirom na to da se slika može efikasno rekonstruirati korištenjem znatno manjeg broja Hermitovih koeficijenata u odnosu na broj originalnih koeficijenata slike, umetanje vodenog žiga zapravo je provedeno u domeni kompresije, uz očuvanje visoke kvalitete slike (velika vrijednost PSNR). Učinkovitost predložene procedure ispitana je eksperimentalno i pokazuje značajnu otpornost na uobičajene napade. Osim uobičajenih, procedura pokazuje robusnost i na geometrijske napade. Predloženi pristup može biti korišten u različitim aplikacijama za zaštitu autorskih prava, naročito u aplikacijama koje ujedno zahtijevaju i kompresiju slike, kao što su multimedijske i internetske aplikacije, daljinsko očitavanje podataka i satelitska snimanja