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Proceedings Paper

Hierarchical indexing using R-trees for replica detection
Author(s): Yannick Maret; David Marimón; Frédéric Dufaux; Touradj Ebrahimi
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Paper Abstract

Replica detection is a prerequisite for the discovery of copyright infringement and detection of illicit content. For this purpose, content-based systems can be an efficient alternative to watermarking. Rather than imperceptibly embedding a signal, content-based systems rely on content similarity concepts. Certain content-based systems use adaptive classifiers to detect replicas. In such systems, a suspected content is tested against every original, which can become computationally prohibitive as the number of original contents grows. In this paper, we propose an image detection approach which hierarchically estimates the partition of the image space where the replicas (of an original) lie by means of R-trees. Experimental results show that the proposed system achieves high performance. For instance, a fraction of 0.99975 of the test images are filtered by the system when the test images are unrelated to any of the originals while only a fraction of 0.02 of the test images are rejected when the test image is a replica of one of the originals.

Paper Details

Date Published: 24 August 2006
PDF: 12 pages
Proc. SPIE 6312, Applications of Digital Image Processing XXIX, 63120I (24 August 2006); doi: 10.1117/12.686956
Show Author Affiliations
Yannick Maret, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
David Marimón, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Frédéric Dufaux, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Touradj Ebrahimi, Ecole Polytechnique Fédérale de Lausanne (Switzerland)


Published in SPIE Proceedings Vol. 6312:
Applications of Digital Image Processing XXIX
Andrew G. Tescher, Editor(s)

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