Abstract
A fast and robust ellipse-detection method based on sorted merging is proposed in this paper. This method first represents the edge bitmap approximately with a set of line segments and then gradually merges the line segments into elliptical arcs and ellipses. To achieve high accuracy, a sorted merging strategy is proposed: the merging degrees of line segments/elliptical arcs are estimated, and line segments/elliptical arcs are merged in descending order of the merging degrees, which significantly improves the merging accuracy. During the merging process, multiple properties of ellipses are utilized to filter line segment/elliptical arc pairs, making the method very efficient. In addition, an ellipse-fitting method is proposed that restricts the maximum ratio of the semimajor axis and the semiminor axis, further improving the merging accuracy. Experimental results indicate that the proposed method is robust to outliers, noise, and partial occlusion and is fast enough for real-time applications.
Highlights
Shape-based object detection is an important topic in the field of computer vision
(2) Parameter LCmin restricts the minimum number of line segments for a legal elliptical arc
(1) A sorted merging strategy is proposed for the merging process of the line segments and elliptical arcs
Summary
Shape-based object detection is an important topic in the field of computer vision. Because they are a commonly appearing shape, ellipses are often seen in many types of artificial and real scenes. Ellipse detection has many applications, including detecting industrial components, iris detection, and detecting traffic signs. Ellipse detection is often used as a component of other computer vision tasks, such as 3D calibration [1] and object recognition [2]. It is a challenging task to detect ellipses in complex scenes.
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