Enhanced Perceptual Distance Functions and Indexing for Near-Replica Image Recognition

The proliferation of digital images, and the widespread distribution of digital data that has been made possible by the Internet, has increased problems associated with copyright infringement on digital images. Watermarking schemes have been proposed to safeguard copyrighted images, but watermarks are vulnerable to image processing and geometric distortions, and may not be very effective. Thus, the content-based detection of pirated images has become an important application. In this paper, we discuss two important aspects of such a near-replica detection system: distance functions for similarity measurement, and scalability. We extend our previous work on perceptual distance functions, which proposed the Dynamic Partial Function (DPF), and present enhanced techniques that overcome limitations of DPF. These techniques include the Thresholding, Sampling and Weighting schemes. Experimental evaluations show superior

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