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Zhang, D., and Chang, S. “Detecting image near-duplicate by stochastic attributed relational graph matching with learning,” In Proceedings of the 12th annual ACM international conference on Multimedia (2004), ACM, pp. 877–884.

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• TITLE: Speed-up Multi-modal Near Duplicate Image Detection

  AUTHORS: Chunlei Yang, Jinye Peng, Jianping Fan

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

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.3 No.1B, January 22, 2013

  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.