Ellipse detection method based on the advanced three point algorithm

Bae-keun Kwon, D. Kang
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引用次数: 2

Abstract

In this paper, we propose a fast ellipse detection method using the geometric properties of three points, which are the components of an ellipse. As many conventional ellipse detection methods carry out the detection using five points, a random selection of such points requires much redundant processing. Accordingly, in order to search for an ellipse with minimum number of points, this paper uses the normal and differential equation of an ellipse which requires three points based on their locations and edge angles. First, in order to reduce the number of candidate edges, the edges are divided into 8 groups depending on the edge angle, and then a new geometric constraint called quadrant condition is introduced for the reduction of noisy candidate edges. Clustering is employed to find prominent candidates in the space of some ellipse parameters. Experiments through real images show that our method satisfies both the reliability and detection speed of ellipse detection.
基于先进三点算法的椭圆检测方法
本文提出了一种利用构成椭圆的三个点的几何特性来快速检测椭圆的方法。由于许多传统的椭圆检测方法都是使用五个点进行检测,因此随机选择这些点需要进行大量冗余处理。因此,为了搜索点数最少的椭圆,本文利用椭圆的法向方程和微分方程,根据椭圆的位置和边角需要三个点。首先,为了减少候选边缘的数量,根据边缘的角度将边缘划分为8组,然后引入一种新的几何约束象限条件来减少有噪声的候选边缘。采用聚类方法在椭圆参数空间中寻找突出的候选参数。实际图像实验表明,该方法既满足椭圆检测的可靠性,又满足椭圆检测的检测速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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