Detection of Microbubbles Using the Hough Transform

Abstract:

The microbubble has been widely used and shown to be effective in various fields. Therefore, there is an importance of measuring accurately its size by image processing techniques. In this paper, we propose a detection method of microbubbles by the approach based on the Hough transform. Experimental results show only 4.49% of the average error rate of the undetected microbubbles and incorrectly detected ones. This low percentage of the error rate shows the effectiveness of the proposed method.

• Periodical: Applied Mechanics and Materials (Volume 378)
• Pages: 478-482
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.378.478
• Online since: August 2013
• Authors: Yoshihiro Mitani, Toshitaka Oki
• Keywords: Hough Transform (HT), Mage Processing Techniques, Microbubble Detection, Size of Microbubble

References

[1] B. Junker: Measurement of bubble and pellet size distributions: past and current image analysis technology, Bioprocess Biosyst Eng, 29, pp.185-206 (2006).

DOI: 10.1007/s00449-006-0070-3

[2] P. V. C. Hough: Methods and means for recognizing complex patterns, US patent 3069654 (1962).

[3] J. Illingworth and J. Kittler: A survey of the Hough transform, Computer Vision, Graphics, and Image Processing, 44, 1, pp.87-116 (1988).

DOI: 10.1016/s0734-189x(88)80033-1

[4] E. Galindo, C. P. Larralde-Corona, T. Brito, M. S. Cordova-Aguilar, B. Taboada, L. Vega-Alvarado, and G. Corkidi: Development of advanced image analysis techniques for the in situ characterization of multiphase dispersions occurring in bioreactors, Journal of Biotechnology, 116, 3, pp.261-270 (2005).

DOI: 10.1016/j.jbiotec.2004.10.018

[5] X. -H. Pan, R. Luo, X. -Y. Yang, and H. -J. Yang: Three-dimensional particle image tracking for dilute particle-liquid flows in a pipe, Measurement Science and Technology, 13, 8, pp.1206-1216 (2002).

DOI: 10.1088/0957-0233/13/8/307

[6] M. Dobes, J. Martinek, D. Skoupil, Z. Dobesova, and J. Pospisil: Human eye localization using the modified Hough transform, Optik, 117, 10, pp.468-473 (2006).

DOI: 10.1016/j.ijleo.2005.11.008

[7] B. Taboada, L. Vega-Alvarado, M. S. Cordova-Aguilar, E. Galindo, and G. Corkidi: Semi-automatic image analysis methodology for the segmentation of bubbles and drops in complex dispersions occurring in bioreactors, Experiments in Fluids, 41, 3, pp.383-392 (2006).

DOI: 10.1007/s00348-006-0159-0

[8] L. Shen, X. Song, M. Iguchi, and F. Yamamoto: A method for recognizing particles in overlapped particle images, Pattern Recognition Letters, 21, pp.21-30 (2000).

DOI: 10.1016/s0167-8655(99)00130-0

[9] S. -H. Chiu and J. -J. Liaw: An effective voting method for circle detection, Pattern Recognition Letters, 26, pp.121-133 (2005).

DOI: 10.1016/j.patrec.2004.09.037

[10] B. Krasovitski and E. Kimmel: Stability of an encapsulated bubble shell, Ultrasonics, 44, pp.216-220 (2006).

DOI: 10.1016/j.ultras.2005.11.003

[11] N. Otsu: A threshold selection method from gray-level histograms, IEEE Trans. Syst. Man Cybern. 9(1), pp.62-66 (1979).

DOI: 10.1109/tsmc.1979.4310076