  The exploitation of traces in JPEG double compressed images is of utter
importance for investigations. Properly exploiting such insights, First
Quantization Estimation (FQE) could be performed in order to obtain source
camera model identification (CMI) and therefore reconstruct the history of a
digital image. In this paper, a method able to estimate the first quantization
factors for JPEG double compressed images is presented, employing a mixed
statistical and Machine Learning approach. The presented solution is
demonstrated to work without any a-priori assumptions about the quantization
matrices. Experimental results and comparisons with the state-of-the-art show
the goodness of the proposed technique.
