Optimization of Input Pattern for Semi Non-Intrusive Component Forensics of Digital Cameras

This paper considers the problem of semi non-intrusive component forensics and proposes a methodology to identify the algorithms and parameters employed by various processing modules inside a digital camera. The proposed analysis techniques assume the availability of the camera; and introduce a forensic methodology to estimate the parameters of the color interpolation and white balancing algorithms employed in cameras. We devise testing conditions, and design good input patterns to improve the overall accuracy in parameter estimation. As demonstrated by the results in the paper, the proposed techniques provide a much lower estimation bias and variance compared to non-intrusive analysis. The features obtained from component forensic analysis provide useful evidence for such applications as analyzing technology evolution trend, detecting technology infringement/licensing, protecting intellectual property rights, and determining camera source.