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Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions pp 541–552Cite as

Fast Image Search by Trees of Keypoint Descriptors

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 364))

Abstract

In this paper, we present a method for fast image searching tree-based representation of local interest point descriptors. Thanks to decreased number of steps needed to perform the search, such a representation of image keypoints is more efficient than the standard, frequently used list representation where images are compared in all-to-all manner. The proposed method generates a tree structure from a set of image descriptors, e.g., generated by the SURF algorithm. The descriptors are stored as leaves in the tree structure and other parent tree nodes are used to group similar descriptors. Each next parent node of the tree forms a wider, more general, group of descriptors. We store average values of the descriptor components in the nodes making it possible to quickly compare sets of descriptors by traversing the tree from the root to a leaf by choosing the smallest deviation between searched descriptor and values of nodes. With each next step of tree traversing we reduce the final number of descriptors that will be needed to compare. The proposed structure also allows to compare whole trees of descriptors what can speed up the process of images comparison, as it involves generating trees of descriptors for single images or for groups of related images accelerating the process of searching for similarities among others.

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Acknowledgments

The project was funded by the National Center for Science under decision number DEC-2011/01/D/ST6/06957. Patryk Najgebauer received a scholarship from the project DoktoRIS—Scholarship program for innovative Silesia co-financed by the European Union under the European Social Fund.

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Authors and Affiliations

  1. Institute of Computational Intelligence, Czȩstochowa University of Technology, al. Armii Krajowej 36, 42-200, Czȩstochowa, Poland

    Patryk Najgebauer & Rafał Scherer

Authors
  1. Patryk Najgebauer
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  2. Rafał Scherer
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Corresponding author

Correspondence to Rafał Scherer .

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Editors and Affiliations

  1. Department of Automatic Control and Biomedical Engineering, AGH University of Science and Technology, Kraków, Poland, and International Centre for Decision Sciences and Forecasting, Kraków, Poland

    Andrzej M.J. Skulimowski

  2. Polish Academy of Sciences, Systems Research Institute, Warszawa, Poland, and AGH University of Science and Technology, Kraków, Poland

    Janusz Kacprzyk

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© 2016 Springer International Publishing Switzerland

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Najgebauer, P., Scherer, R. (2016). Fast Image Search by Trees of Keypoint Descriptors. In: Skulimowski, A., Kacprzyk, J. (eds) Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions. Advances in Intelligent Systems and Computing, vol 364. Springer, Cham. https://doi.org/10.1007/978-3-319-19090-7_41

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  • DOI: https://doi.org/10.1007/978-3-319-19090-7_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19089-1

  • Online ISBN: 978-3-319-19090-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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