title: Forensic identification of resampling operators: A semi non-intrusive approach.
abstract: Recently, several new resampling operators have been proposed and successfully invalidate the existing resampling detectors. However, the reliability of such anti-forensic techniques is unaware and needs to be investigated. In this paper, we focus on the forensic identification of digital image resampling operators including the traditional type and the anti-forensic type which hides the trace of traditional resampling. Various resampling algorithms involving geometric distortion (GD)-based, dual-path-based and postprocessing-based are investigated. The identification is achieved in the manner of semi non-intrusive, supposing the resampling software could be accessed. Given an input pattern of monotone signal, polarity aberration of GD-based resampled signal's first derivative is analyzed theoretically and measured by effective feature metric. Dual-path-based and postprocessing-based resampling can also be identified by feeding proper test patterns. Experimental results on various parameter settings demonstrate the effectiveness of the proposed approach.
authors: Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China. 06112056@bjtu.edu.cn
authors: Gang
authors: G
authors: Cao
authors: Yao
authors: Y
authors: Zhao
authors: Rongrong
authors: R
authors: Ni