Accurate detection of ellipses with false detection control at video rates using a gradient analysis

作者:

Highlights:

• This paper presents an ellipse detection method that combines the advantages of arc extraction and arc grouping to guarantee the effectiveness of ellipse detection and optimizes the computation cost.

• In the step of smooth arc extraction, we propose a novel approach of identifying the precise splitting points (sudden changes) in order to achieve better segmentations from curves to smooth arcs that may belong to ellipses. A coarse search for sudden changes is first performed with a big range, and then such points are determined with a finer scope.

• We present a novel method to estimate the ellipse centre by an iterative mean-shift clustering algorithm, which improves its robustness to noise and obtains a more precise centre comparing the existing methods that determine ellipse centres.

• We adopt the ratio of half of the circumference of the bounding box enclosing an arc and the sum of the semi-axes lengths to measure the integrity of ellipse to improve the detection accuracy.

• We propose a new approach of false determination control to determine detection results based on the intrinsic geometric attribute of ellipse expressed by a mathematical model, which avoids false detections effectively.

摘要

•This paper presents an ellipse detection method that combines the advantages of arc extraction and arc grouping to guarantee the effectiveness of ellipse detection and optimizes the computation cost.•In the step of smooth arc extraction, we propose a novel approach of identifying the precise splitting points (sudden changes) in order to achieve better segmentations from curves to smooth arcs that may belong to ellipses. A coarse search for sudden changes is first performed with a big range, and then such points are determined with a finer scope.•We present a novel method to estimate the ellipse centre by an iterative mean-shift clustering algorithm, which improves its robustness to noise and obtains a more precise centre comparing the existing methods that determine ellipse centres.•We adopt the ratio of half of the circumference of the bounding box enclosing an arc and the sum of the semi-axes lengths to measure the integrity of ellipse to improve the detection accuracy.•We propose a new approach of false determination control to determine detection results based on the intrinsic geometric attribute of ellipse expressed by a mathematical model, which avoids false detections effectively.

论文关键词:Ellipse detection,Geometric approach,Gradient analysis,Centre estimation,Arc classification

论文评审过程:Received 22 October 2017, Revised 1 December 2017, Accepted 23 March 2018, Available online 29 March 2018, Version of Record 7 April 2018.

论文官网地址:https://doi.org/10.1016/j.patcog.2018.03.023