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Subpixel Detection of Circular Objects Using Geometric Property

Authors: Wen-Yen Wu, Wen-Bin Yu


In this paper, we propose a method for detecting circular shapes with subpixel accuracy. First, the geometric properties of circles have been used to find the diameters as well as the circumference pixels. The center and radius are then estimated by the circumference pixels. Both synthetic and real images have been tested by the proposed method. The experimental results show that the new method is efficient.

Keywords: least squares estimation, hough transformation, Subpixel, circle detection

Digital Object Identifier (DOI):

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[1] D. H. Ballard, Generalizing the Hough transform to detect arbitrary shapes, Pattern Recognition, 13, 1981, 111-122.
[2] M. Berman, Large sample bias in least squares estimators of a circular arc center and its radius, Computer Vision, Graphics, and Image Processing, 45, 1989, 126-128.
[3] R. Chan and W. C. Siu, New parallel Hough transformation for circles, IEE Proceedings-E, 138, 1991, 335-344.
[4] F. L. Chen and S. W. Lin, Subpixel estimation of circle parameters using orthogonal circular detector, Computer Vision and Image Understanding, 78, 2000, 206-221.
[5] L. H. Chen and K. L. Lee, A new method for circular object detection and location, Pattern Recognition Letters, 11, 1990, 691-697.
[6] R. S. Conker, A dual plane variation of the Hough transform for detecting non-concentric circles of different radii, Computer Vision, Graphics, and Image Processing, 43, 1988, 115-132.
[7] E. R. Davies, A high speed algorithm for circular object location, Pattern Recognition Letters. 6, 1987, 323-333.
[8] E. R. Davies, A modified Hough scheme for general circle location, Pattern Recognition Letters. 7, 1988, 37-43.
[9] E. R. Davies, A hybrid sequential-parallel approach to accurate circle center location, Pattern Recognition Letters. 7, 1988, 279-290.
[10] R. O. Duda and P. E. Hart, Use of Hough transformation to detect lines and curves in pictures, Communications of the ACM. 15, 1972, 11-15.
[11] J. Y. Goulermas and P. Liatsis, Genetically fine-tuning the Hough transform feature space, for the detection of circular objects, Image and Vision Computing, 16, 1998, 615-625.
[12] N. Guil and E. L. Zapata, Lower order circle and ellipse Hough transform, Pattern Recognition, 30, 1997, 1929-1744.
[13] D. Ioannou, W. Huda, and A. F. Laine, Circle recognition through a 2D Hough transformation and radius histogramming, Image and Vision Computing, 17, 1999, 15-26.
[14] A. Kavianpour and N. Bagherzadeh, Finding circular shapes in an image on a pyramid architecture, Pattern Recognition Letters, 13, 1992, 843-848.
[15] P. Kierkegaard, A method for detection of circular arcs based on the Hough transform, Machine and Vision Applications, 5, 1992, 249-263.
[16] G. Kimme, D. Ballard, and J. Sklansky, Finding circles by an array of accumulators, Communications of the ACM. 18, 1975, 120-122.