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Fine-search for image copy detection based on local affine-invariant descriptor and spatial dependent matching

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Abstract

Copies are somehow a subset of near-duplicates, but the approaches extensively employed in near-duplicate retrieval only obtain rough and imprecise query results. Therefore a fine-search scheme is proposed to refine these rough results and attempt to completely detect the real copies accurately. This scheme first employs a local affine-invariant descriptor based on polar-mapping and discrete Fourier transform. Then a spatial dependent matching method is proposed combining nearest neighbor distance ratio with the spatial relationships among the local features. Experimental results demonstrate that the employed descriptor is more robust, distinctive and suitable for copy detection in comparison with the SIFT descriptor. And the spatial dependent matching is able to improve the recall and precision, and lower the false positives and ambiguities.

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Acknowledgement

This work is supported by NSF of China Grants 60873226, 60803112, National 863 Hi-Tech Grant 2009AA01Z411, and the Electronic Development Fund Grant [2007]329.

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Authors and Affiliations

  1. College of Computer Science, Huazhong University of Science & Technology, Wuhan, China

    Hefei Ling, Liyun Wang & Fuhao Zou

  2. Institute of ECIT, Queen’s University Belfast, Belfast, BT7 1NN, UK

    Weiqi Yan

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  1. Hefei Ling
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  2. Liyun Wang
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  3. Fuhao Zou
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Correspondence to Hefei Ling.

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Ling, H., Wang, L., Zou, F. et al. Fine-search for image copy detection based on local affine-invariant descriptor and spatial dependent matching. Multimed Tools Appl 52, 551–568 (2011). https://doi.org/10.1007/s11042-009-0439-9

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