Re-quantization commonly occurs when digital multimedia content is being tampered with. Detecting requantization
is therefore an important element for assessing the authenticity of digital multimedia content.
In this paper, we introduce three features based on the observation that re-quantization (i) induces periodic
artifacts and (ii) introduces discontinuities in the signal histogram. After validating the discriminative potential
of these features with synthetic signals, we propose a system to detect JPEG re-compression. Both linear (FLD)
and non-linear (SVM) classifications are investigated. Experimental results clearly demonstrate the ability of the
proposed features to detect JPEG re-compression, as well as their competitiveness compared to prior approaches
to achieve the same goal.