Abstract:
A method for the detection of bubble-like transparent objects with multiple interfaces in a liquid is proposed. Depending on the lighting conditions, bubble appearance va...Show MoreMetadata
Abstract:
A method for the detection of bubble-like transparent objects with multiple interfaces in a liquid is proposed. Depending on the lighting conditions, bubble appearance varies significantly, including contrast reversal and multiple inter-reflections. We formulate the bubble detection problem as the detection of Concentric Circular Arrangements (CCA). The CCAs are recovered in a hypothesize-optimize-verify framework. The hypothesis generation proceeds by sampling from the components of the non-maximum suppressed responses of oriented ridge filters followed by CCA parameter estimation. Parameter optimization is carried out by minimizing a novel cost-function by the simplex method. The proposed method for bubble detection showed good performance in an industrial application requiring estimation of gas volume in pulp suspension, achieving 1.5% mean absolute relative error.
Date of Conference: 11-15 November 2012
Date Added to IEEE Xplore: 14 February 2013
ISBN Information:
ISSN Information:
Conference Location: Tsukuba, Japan
References is not available for this document.
Select All
1.
http://www2. it. lut. fi/project/pulpvision/, PulpVision project.
2.
T. Atherton and D. Kerbyson. Size invariant circle detection. IVC, 17(11):795-803, 1999.
3.
J. Canny. A computational approach to edge detection. IEEE PAMI, 8:679-698, 1986.
4.
C. W. Dence and D. W. Reeve. Pulp Bleaching, Principles and Practice. 1996.
5.
M. A. Fischler and R. C. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 24(6):381-395, 1981.
6.
T. Lindeberg. Edge detection and ridge detection with automatic scale selection. In Proc. CVPR, 1996.
7.
L. Pan, W.-S. Chu, J. Saragih, F. De la Torre, and M. Xie. Fast and robust circular object detection with probabilistic pairwise voting. IEEE Signal Processing Letters, 18(11):639-642, 2011.
8.
W. Press, B. Flannery, S. Teukolsky, and W. Vetterling. Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press, 1992.
9.
L. Vega-Alvarado, B. Taboada, E. Galindo, and G. Corkidi. Hough transform based method for air bubbles and oil drops segmentation in dispersions occurring in stirred bioreactors. In Proc. 25th Annual Int. Conf. of IEEE Eng. in Medicine and Biology Society, 2003.
10.
P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. In Proc. CVPR, 2001.
11.
E. Zelniker and I. Clarkson. Maximum-likelihood estimation of circle parameters via convolution. IEEE TIP, 15(4):865-876, 2006.