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MyFinder: near-duplicate detection for large image collections

Published: 19 October 2009 Publication History

Abstract

The explosive growth of multimedia data poses serious challenges to data storage, management and search. Efficient near-duplicate detection is one of the required technologies for various applications. In this paper, we introduce MyFinder, an image near-duplicate detection system for large image collections. MyFinder consists of three major components: 1) a local-feature-based image representation utilizing the proposed LDP (Local-Difference-Pattern) feature, 2) the Locality-Sensitive-Hashing (LSH) as the core indexing structure to assure the most frequent data access occurred in the main memory, and 3) multi-step verification for queries to best exclude false positives and to increase the precision.

References

[1]
Y. Ke, R. Sukthankar, and L. Huston. Efficient Near-duplicate Detection and Sub-image Retrieval. In Proceedings of ACM International Conference on Multimedia, 2004, pages 869--876.
[2]
A. Gionis, P. Indyk, and R. Motwani. Similarity search in high dimensions via hashing. In Proceedings of International Conference on Very Large Databases, 1999.
[3]
CGFA - A Virtual Art Museum. http://cgfa.sunsite.dk/
[4]
D. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 2004
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B. Thomee, M. J. Huiskes, E. M. Bakker, and Michael S. Lew. Large scale image copy detection evaluation. In Proceedings of ACM International Conference on Multimedia Information Retrieval, 2008, pages 59--66

Cited By

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  • (2017)Evaluating robustness of perceptual image hashing algorithms2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)10.23919/MIPRO.2017.7973569(995-1000)Online publication date: May-2017
  • (2012)Spatial Locality Weighting of Features Using Saliency Map with a Bag-of-Visual-Words Approach2012 IEEE 24th International Conference on Tools with Artificial Intelligence10.1109/ICTAI.2012.151(1070-1075)Online publication date: Nov-2012
  • (2011)Partial near-duplicate image identification with global geometric consistency of subset-of-featuresProceedings of 2011 International Conference on Computer Science and Network Technology10.1109/ICCSNT.2011.6182523(2700-2704)Online publication date: Dec-2011

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  1. MyFinder: near-duplicate detection for large image collections

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    Published In

    cover image ACM Conferences
    MM '09: Proceedings of the 17th ACM international conference on Multimedia
    October 2009
    1202 pages
    ISBN:9781605586083
    DOI:10.1145/1631272

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 19 October 2009

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    Author Tags

    1. database retrieval
    2. image feature
    3. near-duplicate detection

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    MM09
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    MM09: ACM Multimedia Conference
    October 19 - 24, 2009
    Beijing, China

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    Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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    Cited By

    View all
    • (2017)Evaluating robustness of perceptual image hashing algorithms2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)10.23919/MIPRO.2017.7973569(995-1000)Online publication date: May-2017
    • (2012)Spatial Locality Weighting of Features Using Saliency Map with a Bag-of-Visual-Words Approach2012 IEEE 24th International Conference on Tools with Artificial Intelligence10.1109/ICTAI.2012.151(1070-1075)Online publication date: Nov-2012
    • (2011)Partial near-duplicate image identification with global geometric consistency of subset-of-featuresProceedings of 2011 International Conference on Computer Science and Network Technology10.1109/ICCSNT.2011.6182523(2700-2704)Online publication date: Dec-2011

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