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CBIR Service for Object Identification

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Computer Vision Systems (ICVS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9163))

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Abstract

This paper proposes an architecture for an exact object detection system. The implementation as well as the communication between individual system components is detailed in the paper. Well known methods for feature detection and extraction were used. Fast and precise method for feature comparison is presented.

The proposed system was evaluated by training the dataset and querying the dataset. With 12 Workers, the response time of querying the dataset consisting of \(100\,000\) images were just below 20 seconds. Also system trained dataset of this size with same amount of workers in about an hour.

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Notes

  1. 1.

    http://storm.apache.org/.

  2. 2.

    https://www.mongodb.org/.

  3. 3.

    http://www.rabbitmq.com/.

  4. 4.

    http://press.liacs.nl/mirflickr/.

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Acknowledgments

This research has been supported by the grant MV0 VF20132015030.

Author information

Authors and Affiliations

  1. ProTyS, a.s., Václavská 12/316, 120 00, Praha 2, Czech Republic

    Josef Hák & Martin Klíma

  2. CertiCon a.s., Evropská 11, 160 00, Praha 6, Czech Republic

    Mikuláš Krupička & Václav Čadek

Authors
  1. Josef Hák
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  2. Martin Klíma
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  3. Mikuláš Krupička
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  4. Václav Čadek
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Corresponding author

Correspondence to Mikuláš Krupička .

Editor information

Editors and Affiliations

  1. Aalborg University, Copenhagen, Denmark

    Lazaros Nalpantidis

  2. Aalborg University, Copenhagen, Denmark

    Volker Krüger

  3. Royal Institute of Technology - KTH, Stockholm, Sweden

    Jan-Olof Eklundh

  4. Democritus University of Thrace, Xanthi, Greece

    Antonios Gasteratos

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Hák, J., Klíma, M., Krupička, M., Čadek, V. (2015). CBIR Service for Object Identification. In: Nalpantidis, L., Krüger, V., Eklundh, JO., Gasteratos, A. (eds) Computer Vision Systems. ICVS 2015. Lecture Notes in Computer Science(), vol 9163. Springer, Cham. https://doi.org/10.1007/978-3-319-20904-3_47

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  • DOI: https://doi.org/10.1007/978-3-319-20904-3_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20903-6

  • Online ISBN: 978-3-319-20904-3

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