Detection of shifted double JPEG compression by an adaptive DCT coefficient model

Abstract

In many JPEG image splicing forgeries, the tampered image patch has been JPEG-compressed twice with different block alignments. Such phenomenon in JPEG image forgeries is called the shifted double JPEG (SDJPEG) compression effect. Detection of SDJPEG-compressed patches could help in detecting and locating the tampered region. However, the current SDJPEG detection methods do not provide satisfactory results especially when the tampered region is small. In this paper, we propose a new SDJPEG detection method based on an adaptive discrete cosine transform (DCT) coefficient model. DCT coefficient distributions for SDJPEG and non-SDJPEG patches have been analyzed and a discriminative feature has been proposed to perform the two-class classification. An adaptive approach is employed to select the most discriminative DCT modes for SDJPEG detection. The experimental results show that the proposed approach can achieve much better results compared with some existing approaches in SDJPEG patch detection especially when the patch size is small.

Tampering Localization in Double Compressed Images by Investigating Noise Quantization

“…Lin, He, Tang, & Tang (2009) recognized the periodicity in the histogram of double quantized DCT coefficients and utilized it for double compression detection. Wang, Liew, Li, Zhang, & Li (2014) also used the distribution of DCT coefficient histogram for differentiating the NADJPEG compressed region from single compressed region. Wu, Kong, Wang, & Shang (2013) used difference of pixels inside and at the edges of the 8 8 × blocks to identify the double compression.…”