• image copy detection;
  • geometric transformations;
  • distribution characteristics;
  • global signatures;
  • local signatures;
  • interest points


To prevent digital image from unauthorized use, image copy detection is an important technique in the field of copyright protection. The conventional methods of image copy detection concentrate on extracting global or local signatures to resist various kinds of copy attacks. However, the global signatures are sensitive to some geometric transformations, such as rotation and cropping, while the local signatures are not discriminative enough to identify copies from similar images. Considering both the robustness and discriminability, a novel image signature based on the combination of global and local signatures is proposed for image copy detection. Firstly, the interest points are detected from a given image by using the Hessian–Affine detector. Secondly, the image is divided into some circle tracks, and thus the interest points are distributed into these tracks. Finally, to combine the advantages of the circle-track-based global signature and the interest points, the global distribution characteristics of interest points based on circle tracks are used to generate our image signature. Experimental results demonstrate the effectiveness of our proposed method in the aspects of both robustness and discriminability. Copyright © 2013 John Wiley & Sons, Ltd.