Image copy detection based on SVD in wavelet domain

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.