Abstract: With the advancement of digital image processing, image tampering techniques have grown increasingly diverse and covert, among which object removal is a critical manipulation technique. Seam Carving, initially designed for content-aware resizing of images, can also be exploited for object removal. To address this tampering technique, this paper proposes a novel forensic method to localize object removal by Seam Carving by analyzing anomalies in DCT coefficients. For the first time, the paper introduces the double quantization effect into object removal by Seam Carving. Specifically, the paper identifies abnormal DCT blocks generated during Seam Carving-based object removal. The proposed method involves three key steps: 1) extracting the quantization matrix and DCT coefficient histograms from JPEG images; 2) estimating the primary quantization matrix and original DCT coefficients based on histograms, followed by generating a posterior probability map of tampered regions using a Bayesian framework; 3) denoising and thresholding the probability map to pinpoint the location of removed objects. Experimental results demonstrate that the proposed method effectively detects and localizes Seam Carving object removal. This method provides a new research direction for tampering forensics. 

Key words: image forensics, tampering detection, object removal, Seam Carving, double quantization effect