Comparison of Appearance-Based and Geometry-Based Bubble Detectors

  • Nataliya Strokina
  • Roman Juránek
  • Tuomas Eerola
  • Lasse Lensu
  • Pavel Zemčik
  • Heikki Kälviäinen
Conference paper

DOI: 10.1007/978-3-319-11331-9_73

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8671)
Cite this paper as:
Strokina N., Juránek R., Eerola T., Lensu L., Zemčik P., Kälviäinen H. (2014) Comparison of Appearance-Based and Geometry-Based Bubble Detectors. In: Chmielewski L.J., Kozera R., Shin BS., Wojciechowski K. (eds) Computer Vision and Graphics. ICCVG 2014. Lecture Notes in Computer Science, vol 8671. Springer, Cham

Abstract

Bubble detection is a complicated tasks since varying lighting conditions changes considerably the appearance of bubbles in liquid. The two common techniques to detect circular objects such as bubbles, the geometry-based and appearance-based approaches, have their advantages and weaknesses. The geometry-based methods often fail to detect small blob-like bubbles that do not match the used geometrical model, and appearance-based approaches are vulnerable to appearance changes caused by, e.g., illumination. In this paper, we compare a geometry-based concentric circular arrangements (CCA) and appearance-based sliding window methods as well as their combinations in terms of bubble detection, gas volume computation, and size distribution estimation. The best bubble detection performance was achieved with the sliding window method whereas the most precise volume estimate was produced by the CCA method. The combination of the two approaches gave only a minor advantage compared to the base methods.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nataliya Strokina
    • 1
  • Roman Juránek
    • 2
  • Tuomas Eerola
    • 3
  • Lasse Lensu
    • 3
  • Pavel Zemčik
    • 2
  • Heikki Kälviäinen
    • 3
  1. 1.Department of Signal ProcessingTampere University of TechnologyTampereFinland
  2. 2.Department of Computer Graphics and MultimediaBrno University of TechnologyBrnoCzech Republic
  3. 3.Machine Vision and Pattern Recognition LaboratoryLappeenranta University of TechnologyLappeenrantaFinland

Personalised recommendations