Detecting Double JPEG Compressed Color Images via an Improved Approach

Detecting double Joint Photographic Experts Group (JPEG) compressionfor color images is vital in the field of image forensics. In previousresearches, there have been various approaches to detecting double JPEGcompression with different quantization matrices. However, the detectionof double JPEG color images with the same quantization matrix is stilla challenging task. An effective detection approach to extract features isproposed in this paper by combining traditional analysis with ConvolutionalNeural Networks (CNN). On the one hand, the number of nonzero pixels andthe sum of pixel values of color space conversion error are provided with 12-dimensional features through experiments. On the other hand, the roundingerror, the truncation error and the quantization coefficient matrix are used togenerate a total of 128-dimensional features via a specially designed CNN. Insuch aCNN, convolutional layers with fixed kernel of 1×1 and Dropout layersare adopted to prevent overfitting of the model, and an average pooling layeris used to extract local characteristics. In this approach, the Support VectorMachine (SVM) classifier is applied to distinguishwhether a given color imageis primarily or secondarily compressed. The approach is also suitable for thecase when customized needs are considered. The experimental results showthat the proposed approach is more effective than some existing ones whenthe compression quality factors are low.

Detecting JPEG image forgery based on double compression

Detecting the forgery parts from a double compressed image is very important and urgent work for blind authentication. A very simple and efficient method for accomplishing the task is proposed. Firstly, the probabilistic model with periodic effects in double quantization is analyzed, and the probability of quantized DCT coefficients in each block is calculated over the entire iraage. Secondly, the posteriori probability of each block is computed according to Bayesian theory and the results mentioned in first part. Then the mean and variance of the posteriori probability are to be used for judging whether the target block is tampered. Finally, the mathematical morphology operations are performed to reduce the false alarm probability. Experimental results show that the method can exactly locate the doctored part, and through the experiment it is also found that for detecting the tampered regions, the higher the second compression quality is, the more exact the detection efficiency is.

An Overview of Double JPEG Compression Detection and Anti-detection

JPEG(Joint Image Experts Group)is currently the most widely used image format on the Internet.Existing cases show that many tampering operations occur on JPEG images.The basic process of the operation is that the JPEG file is first decompressed,modified in the null field,and then the tampered image is compressed and saved in JPEG format,so that the tampered image may be compressed several times.Therefore,the double compression detection of JPEG images can be an important part for determining whether an image has been tampered with,and the study of double JPEG compression anti-detection can further advance the progress of detection work.In this paper,we mainly review the literature in the field of double JPEG compression detection in recent years with two aspects,namely,the quantization table remains unchanged and the quantization table is inconsistent in the double JPEG compression process,Also,we will introduce some representative methods of double JPEG anti-detection in recent years.Finally,we analyze the problems existing in the field of double JPEG compression and give an outlook on the future development direction.