This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
A Method to Detect and Characterize Ellipses Using the Hough Transform
July 1999 (vol. 21 no. 7)
pp. 652-657

Abstract—In this paper we describe a new technique for detecting and characterizing ellipsoidal shapes automatically from any type of image. This technique is a single pass algorithm which can extract any group of ellipse parameters or characteristics which can be computed from those parameters without having to detect all five parameters for each ellipsoidal shape. Moreover, the method can explicitly incorporate any a priori knowledge the user may have concerning ellipse parameters. The method is based on techniques from Projective Geometry and on the Hough Transform. This technique can significantly reduce interpretation and computation time by automatically extracting only those features or geometric parameters of interest from images and making exact use of a priori information.

[1] J. Cabrera and P. Meer, "Unbiased Estimation of Ellipses by Bootstrapping," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 7, pp. 752-756, July 1996.
[2] J. Canny, “A Computational Approach to Edge Detection,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679-698, June 1986.
[3] J. Hall, M. Ponzi, M. Gonfalini, and G. Maletti, "Automatic Extraction and Characterization of Geological Features and Textures From Borehole Images and Core Photographs," Trans. SPWLA 37th Ann. Logging Symp., 1996.
[4] P.V.C. Hough, "Method and Means for Recognizing Complex Patterns," U.S. Patent 3,069,654, Dec.18 1962.
[5] J. Illingworth and J. Kitter, "A survey of Hough transform," CVGIP, vol. 44, pp. 87-116, 1988.
[6] H. Kalviainen and P. Hirvonen, "An Extension of the Randomized Hough Transform Exploiting Connectivity," Pattern Recognition Letters, vol. 18, no. 1, pp. 77-85, 1997.
[7] R. Kirsch, "Computer Determination of the Constituent Structure of Biological Images," Computers and Biomedical Res., vol. 4, pp. 315-328, 1971.
[8] V.F. Leavers, "The Dynamic Generalized Hough Transform: Its Relationship to the Probabilistic Hough Transforms and an Application to the Concurrent Detection of Circles and Ellipses," CVGIP: Image Understanding, vol. 56, no. 3, pp. 381-398, Nov. 1992.
[9] E.P. Lyvers and O.R. Mitchell, “Precision Edge Contrast and Orientation Estimation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 10, no. 6, pp. 927-937, 1988.
[10] S. Mallat and S. Zhong, “Characterization of Signals from Multiscale Edges,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 7, pp. 710-732, July 1992.
[11] D. Marr and E. Hildreth, "Theory of Edge Detection," vol. 207, series B, pp. 187-217, Proc. Royal Soc. London, 1980.
[12] E.A. Maxwell, The Methods of Plane Projective Geometry Based on the Use of General Homogeneous Coordinates.Cambridge, England: Cambridge Univ. Press, 1946.
[13] H. Muammar and M. Nixon, "Tristage Hough Transform for Multiple Ellipse Extraction," IEE Proc.-E, vol. 138, no. 1, pp. 27-35, Jan. 1991.
[14] D. Scott, "Average Shifted Histograms: Effective Nonparametric Density Estimators in Several Dimensions," Annals of Statistics, vol. 13, no. 3, pp. 1,024-1,040, 1985.
[15] D. Shaked, O. Yaron, and N. Kiryati, “Deriving Stopping Rules for the Probabilistic Hough Transform by Sequential Analysis,” Computer Vision and Image Understanding, vol. 63, pp. 512-526, 1996.
[16] M. Soffer and N. Kiryati, "Guaranteed Convergence of the Hough Transform," Computer Vision and Image Understanding, vol. 69, no. 2, pp. 119-134, 1998.
[17] H. Tsukune and K. Goto, "Extracting Elliptical Figures From an Edge Vector Field," IEEE Computer Vision and Pattern Recognition Conf.,New York, 1983.
[18] H. Yuen, J. Illingworth, and J. Kittler, "Ellipse Detection Using the Hough Transform," AVC88: Proc. Fourth Alvey Vision Conf., 1988.
[19] D. Ziou and A. Koukam, "Knowledge-Based Assistant for the Selection of Edge Detectors," Pattern Recognition, vol. 31, no. 5, pp. 587-596, 1998.

Index Terms:
Hough Transform, ellipse detection, parameter estimation, projective geometry, feature extraction, computer vision.
Citation:
Nick Bennett, Robert Burridge, Naoki Saito, "A Method to Detect and Characterize Ellipses Using the Hough Transform," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 7, pp. 652-657, July 1999, doi:10.1109/34.777377
Usage of this product signifies your acceptance of the Terms of Use.