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Partition Min-Hash for Partial Duplicate Image Discovery

  • David C. Lee
  • Qifa Ke
  • Michael Isard
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6311)

Abstract

In this paper, we propose Partition min-Hash (PmH), a novel hashing scheme for discovering partial duplicate images from a large database. Unlike the standard min-Hash algorithm that assumes a bag of words image representation, our approach utilizes the fact that duplicate regions among images are often localized. By theoretical analysis, simulation, and empirical study, we show that PmH outperforms standard min-Hash in terms of precision and recall, while being orders of magnitude faster. When combined with the start-of-the-art Geometric min-Hash algorithm, our approach speeds up hashing by 10 times without losing precision or recall. When given a fixed time budget, our method achieves much higher recall than the state-of-the-art.

Keywords

Hash Function Image Retrieval Visual Word Hash Table Query Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • David C. Lee
    • 1
  • Qifa Ke
    • 2
  • Michael Isard
    • 2
  1. 1.Carnegie Mellon University 
  2. 2.Microsoft Research Silicon Valley 

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