A decomposable parameter space for the detection of ellipses
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 951-958 |
Journal / Publication | Pattern Recognition Letters |
Volume | 14 |
Issue number | 12 |
Publication status | Published - Dec 1993 |
Externally published | Yes |
Link(s)
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.
In: Pattern Recognition Letters, Vol. 14, No. 12, 12.1993, p. 951-958.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review