Detecting doubly compressed JPEG images by using Mode Based First Digit Features

Bin Li, Yun Q. Shi, Jiwu Huang

Abstract: In this paper, we utilize the probabilities of the first digits of quantized DCT (Discrete Cosine Transform) coefficients from individual AC (Alternate Current) modes to detect doubly compressed JPEG images. Our proposed features, named by Mode Based First Digit Features (MBFDF), have been shown to outperform all previous methods on discriminating doubly compressed JPEG images from singly compressed JPEG images. Furthermore, combining the MBFDF with a multi-class classification strategy can be exploited to identify the quality factor in the primary JPEG compression, thus successfully revealing the double JPEG compression history of a given JPEG image.