Blind Resynchronization for Source Camera Identification in Digitally Zoomed Images

Source Camera Identification (SCI) plays a vital role in digital image forensics by verifying the origin of images in criminal investigations and intellectual property protection. However, the growing use of digital zoom in modern imaging devices introduces geometric distortions that significantly degrade the performance of traditional PRNU-based SCI methods. Existing techniques often rely on brute-force searches over a wide range of zoom scales, resulting in high computational cost and limited robustness. In this paper, we propose a blind resynchronization method that efficiently estimates the digital zoom factor through a fast resampling-based algorithm. The estimated factor is then used to proportionally rescale the test image, enabling accurate alignment with the reference fingerprint. This approach enhances correlation reliability and reduces errors caused by scale mismatch. Experiments conducted on the ForensiCam-215K dataset demonstrate that the proposed method significantly improves identification accuracy while maintaining high efficiency, making it suitable for practical forensic applications involving digitally zoomed content.