000087375 001__ 87375
000087375 005__ 20180127200332.0
000087375 037__ $$aCONF
000087375 245__ $$aA Novel Replica Detection System using Binary Classifiers, R-trees, and PCA
000087375 269__ $$a2006
000087375 260__ $$bIEEE$$c2006
000087375 336__ $$aConference Papers
000087375 490__ $$aParallel Computing in Electrical Engineering
000087375 520__ $$aReplica detection is a prerequisite for the discovery of copyright infringement and detection of illicit content. For this purpose, contentbased systems can be an efficient alternative to watermarking. Rather than imperceptibly embedding a signal, content-based systems rely on image similarity. Certain content-based systems use adaptive classifiers to detect replicas. In such systems, a suspect image is tested against every original, which can become computationally prohibitive as the number of original images grows. In this paper, we propose using R-tree indexing to decrease the necessary number of comparisons and rapidly select the most likely originals. Experimental results show that the proposed system performs very satisfactorily and that up to 99.7% of the originals can be discarded before applying the binary classifiers.
000087375 6531_ $$aCopyright protection
000087375 6531_ $$aImage analysis
000087375 6531_ $$aImage classification
000087375 6531_ $$aImage databases
000087375 6531_ $$aIndexes
000087375 6531_ $$aLTS1
000087375 700__ $$0241059$$aMaret, Y.$$g128747
000087375 700__ $$aNikolopoulos, S.
000087375 700__ $$0241060$$aDufaux, F.$$g149769
000087375 700__ $$0240223$$aEbrahimi, T.$$g105043
000087375 700__ $$aNikolaidis, N.
000087375 773__ $$tInternational Conference on Image Processing
000087375 8564_ $$iINTERNAL$$uhttps://infoscience.epfl.ch/record/87375/files/Maret2006_1478.pdf$$xPUBLIC$$zn/a
000087375 909C0 $$0252397$$pLTS
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000087375 909CO $$ooai:infoscience.tind.io:87375$$pSTI$$pconf
000087375 937__ $$aLTS-CONF-2006-018
000087375 970__ $$aMaret2006_1478/LTS
000087375 973__ $$aEPFL$$sPUBLISHED
000087375 980__ $$aCONF