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A novel image copy detection scheme based on the local multi-resolution histogram descriptor

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Abstract

The conventional research on the image copy detection concentrates on extracting features which are robust enough to resist various kinds of image attacks. However, the global features are sensitive to geometric attacks, especially cropping and rotation, while the local features cannot substantially represent the image spatial information and structure context. Instead of simply extracting feature from local region or global image directly, we propose a novel image copy detection scheme based on Scale Invariant Feature Transform (SIFT) detector and multi-resolution histogram descriptor (MHD). In this novel algorithm, a series of robust, homogenous and large size circular patches are firstly constructed using the SIFT detector, and then the MHD is introduced to generate a discriminative feature vector for each patch. Experimental results obtained from the benchmark attacks demonstrate that the performance of the proposed approach is better than existing methods, especially on the test against geometric distortions.

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Acknowledgments

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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Correspondence to Hefei Ling.

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Xu, Z., Ling, H., Zou, F. et al. A novel image copy detection scheme based on the local multi-resolution histogram descriptor. Multimed Tools Appl 52, 445–463 (2011). https://doi.org/10.1007/s11042-009-0438-x

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