Abstract
Since JPEG has been a popularly used image compression standard, tampering detection in JPEG images now plays an important role. Tampering on compressed images often involve recompression and tend to erase those tampering traces existed in uncompressed images. We could, however, try to discover new traces caused by recompression and use these traces to detect the recompression tampering. The artifacts introduced by lossy JPEG compression can be seen as an inherent signature for recompressed images. In this thesis, we first propose a robust tampered image detection approach by periodicity analysis with the compression artifacts both in spatial and DCT domain. To locate the forged regions, we then propose a forged regions localization method via quantization noise model and image restoration techniques. Finally, we conduct a series of experiments to demonstrate the validity of the proposed periodic features and quantization noise model, which all outperform the existing methods. Also, we show the effectiveness and feasibility of our forged regions localization method with proposed image restoration techniques.