A DECOMPOSABLE PARAMETER SPACE FOR THE DETECTION OF ELLIPSES

Hough transform is a well-known method for detecting parametric curves in binary images. One major drawback of the method is that the transform requires time and memory space exponential in the number of parameters of the curves. An effective approach to reduce both the time and space requirement is the parameter space decomposition. In this paper, we present two methods for the detection of ellipses based on the straight line Hough transform (SLHT). The SLHT of a curve in the theta-rho space can be expressed as the sum of two terms, namely, the translation term, and the intrinsic term. One useful property of this representation is that it allows the translation, rotation and intrinsic parameters of the curve be separated easily. Timing performance of the proposed methods compares favorably with the other Hough-based methods.