Speed-up Multi-modal Near Duplicate Image Detection

Chunlei Yang, Jinye Peng, Jianping Fan

1CSIRO Sustainable Ecosystems, Carmody Road, St. Lucia Queensland, Australia 2CSIRO Sustainable Ecosystems, Highett, Australia.
CSIRO Sustainable Ecosystems, Highett, Australia.

DOI: 10.4236/ojapps.2013.31B004                

Abstract

Near-duplicate image detection is a necessary operation to refine image search results for efficient user exploration. The existences of large amounts of near duplicates require fast and accurate automatic near-duplicate detection methods. We have designed a coarse-to-fine near duplicate detection framework to speed-up the process and a multi-modal integra-tion scheme for accurate detection. The duplicate pairs are detected with both global feature (partition based color his-togram) and local feature (CPAM and SIFT Bag-of-Word model). The experiment results on large scale data set proved the effectiveness of the proposed design.

Keywords

Near-Duplicate Detection; Coarse-To-Fine Framework; Multi-Modal Feature Integration

Conflicts of Interest

The authors declare no conflicts of interest.

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