.png){kind=icon}
.png){kind=icon}
Return
A robust circle detection algorithm based on top-down least-square fitting analysis
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compeleceng.2014.03.011.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, we propose a robust and efficient circle detector, which achieves accurate results with a controlled number of false detections and requires no parameter tuning. The proposed algorithm consists of three steps as follows. First, we propose a novel edge point chaining method to extract Canny edge segments (i.e., contiguous and sequential chains of Canny edge points). Second, we split each edge segment into several smooth sub-segments, and detect candidate circles within each obtained sub-segment based on top-down least-square fitting analysis. Third, we employ Desolneux et al.'s method to reject the false detections. Experimental results demonstrate that the proposed method is efficient and more robust than the state-of-the-art algorithm EDCircles. (c) 2014 Elsevier Ltd. All rights reserved.
Keywords:
HOUGH TRANSFORM
IMAGES
EDGE
Journal
C
IF:
4.9
Papers:
6.7K
Citations:
1.3W