Image Copy Detection Via Grouping In Feature Space Based On Virtual Prior Attacks
2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS(2006)
摘要
In the past, many researches on image copy detection focused on finding a feature that is robust enough for various kinds of image attacks. But it is difficult to find a globally effective feature that is appropriate for many situations. In this paper, we introduce a classification framework to this problem, instead of solving the feature-selection problem. In our approach, novel features are generated by applying virtual prior attacks to copyrighted images, and the copy-detection problem is converted to a classification one that is more robust to solve. Our approach can combine existing image copy detectors and further raise their performances.
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关键词
image copy detection,pattern classification,Gaussian mixture model,ordinal measure,extended feature set
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