A decomposable parameter space for the detection of ellipses

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)951-958
Journal / PublicationPattern Recognition Letters
Volume14
Issue number12
Publication statusPublished - Dec 1993
Externally publishedYes

Abstract

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 θ-π 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 parametersof the curve be separated easily. Timing performance of the proposed methods compares favorably with the other Hough-based methods. © 1993.

Research Area(s)

  • ellipses detection, Hough transform, parameter space decomposition

Citation Format(s)

A decomposable parameter space for the detection of ellipses. / Pao, Derek; Li, H. F.; Jayakumar, R.

In: Pattern Recognition Letters, Vol. 14, No. 12, 12.1993, p. 951-958.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review