关键词: 基于内容的拷贝检测, 数字图像取证, 奇异值分解, 数字版权管理, 多尺度小波分析

Abstract: This paper presented a novel Content-Based Copy Detection (CBCD) scheme using Singular Value Decomposition (SVD) in the wavelet domain and early fusion for passive image forensics and Digital Rights Management (DRM). To improve the efficiency of image descriptors, multiscale singular value vectors combining global and local features of an image were exploited to generate the signature set for comparison. Local features were extracted by image partitioning and Largest Singular Value (LSV). Experimental results demonstrate the proposed algorithm not only achieves good robustness and discriminability in identifying various modified versions of an original image including geometric transformation, signal processing, image manipulation, and the combination of those but also offers improved detection performance in dealing with various rotations, shiftings, and cutting the area of an image. The proposed approach is applied to detect pirated copies of digital images in a database or Internet.

Key words: Content-Based Copy Detection (CBCD), digital image forensics, Singular Value Decomposition (SVD), Digital Rights Management (DRM), multiscale wavelet analysis