Comparative study of Hough Transform methods for circle finding

Abstract A variety of circle detection methods which are based on variations of the Hough Transform are investigated. The five methods considered are the standard Hough Transform, the Fast Hough Transform of Li et al. 1 , a two stage Hough method, and two space saving approaches based on the method devised by Gerig and Klein 2 . The performance of each of the methods has been compared on synthetic imagery and real images from a metallurgical application. Figures and comments are presented concerning the accuracy, reliability, computational efficiency and storage requirements of each of the methods.

[1]  Josef Kittler,et al.  The Adaptive Hough Transform , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Guido Gerig,et al.  FAST CONTOUR IDENTIFICATION THROUGH EFFICIENT HOUGH TRANSFORM AND SIMPLIFIED INTERPRETATION STRATEGY. , 1986 .

[4]  Hungwen Li,et al.  Fast Hough transform: A hierarchical approach , 1986, Comput. Vis. Graph. Image Process..

[5]  E. R. Davies,et al.  A modified Hough scheme for general circle location , 1988, Pattern Recognit. Lett..

[6]  Jack Sklansky,et al.  Finding circles by an array of accumulators , 1975, Commun. ACM.

[7]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[8]  Josef Kittler,et al.  Shape detection using the adaptive Hough transform , 1988 .