A fast and robust circle detection method using isosceles triangles sampling

作     者：Zhang, Hanqing Wiklund, Krister Andersson, Magnus 

作者机构：Umea Univ Dept Phys Linneaus Vaeg 9 SE-90187 Umea Sweden 

出 版 物：《PATTERN RECOGNITION》 (图形识别)

年 卷 期：2016年第54卷

页      面：218-228页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Swedish Research Council [2013-5379] 

主　　题：Circle detection Randomized algorithm Sampling strategy Isosceles triangles 

摘      要：Circle detection using randomized sampling has been developed in recent years to reduce computational intensity. However, randomized sampling is sensitive to noise that can lead to reduced accuracy and false-positive candidates. To improve on the robustness of randomized circle detection under noisy conditions this paper presents a new methodology for circle detection based upon randomized isosceles triangles sampling. It is shown that the geometrical property of isosceles triangles provides a robust criterion to find relevant edge pixels which, in turn, offers an efficient means to estimate the centers and radii of circles. For best efficiency, the estimated results given by the sampling from individual connected components of the edge map were analyzed using a simple clustering approach. To further improve on the accuracy we applied a two-step refinement process using chords and linear error compensation with gradient information of the edge pixels. Extensive experiments using both synthetic and real images have been performed. The results are compared to leading state-of-the-art algorithms and it is shown that the proposed methodology has a number of advantages: it is efficient in finding circles with a low number of iterations, it has high rejection rate of false-positive circle candidates, and it has high robustness against noise. All this makes it adaptive and useful in many vision applications. (C) 2015 Elsevier Ltd. All rights reserved.