DocumentCode
708196
Title
Ellipse detection method based on the advanced three point algorithm
Author
Bae-keun Kwon ; Dong-joong Kang
Author_Institution
Sch. of Mech. Eng., Pusan Nat. Univ., Pusan, South Korea
fYear
2015
fDate
28-30 Jan. 2015
Firstpage
1
Lastpage
5
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.
Keywords
edge detection; pattern clustering; advanced three point algorithm; clustering; differential equation; edge angle; ellipse detection method; geometric constraint; noisy candidate edge reduction; normal equation; quadrant condition; Clustering algorithms; Clutter; Image edge detection; Image resolution; Noise measurement; Plastics; Reliability; Ellipse detection; Mean-shift clustering; Quadrant Constraint; Three-point algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Frontiers of Computer Vision (FCV), 2015 21st Korea-Japan Joint Workshop on
Conference_Location
Mokpo
Type
conf
DOI
10.1109/FCV.2015.7103741
Filename
7103741
Link To Document