Speed up duplicate/near-duplicate image detection

Finding duplicate and near-duplicate images plays an important role on redundancy reduction for image storage, summarization and recommendation. This paper introduces how to speed up Duplicate/Near-Duplicate(D/ND) image detection. Image clustering was first applied to partition the images into multiple groups by using coarse visual features; pair-wise image matching was further applied on the images within the same cluster by using fine visual features such as interesting point descriptors. Our coarse-to-fine method can dramatically reduce the computation cost while achieving comparable detection accuracy rate.

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