Adaptive image replica detection based on support vector classifiers

This paper presents a system for image replica detection. The idea behind the proposed approach is to adapt a system for detecting the replica of a specific reference image. The system is then able to classify test images as replicas of the reference image or as unrelated images. More precisely, the test procedure is as follows. A set of features is extracted from a test image, representing texture, colour and grey-level characteristics. These features are then feed into a preprocessing step, which is fine-tuned to the reference image. Finally, the resulting features are entered to a support vector classifier that determines if the test image is a replica of the reference image. Experimental results show the effectiveness of the proposed system. Target applications include search for copyright infringement (e.g. variations of copyrighted images) and known illicit content (e.g. paedophile images known to the police).