Title :
A survey on ellipse detection methods
Author :
Wong, Y. ; Lin, S.C.F. ; Ren, T.R. ; Kwok, N.M.
Author_Institution :
Sch. of Mech. & Manuf. Eng., Univ. of New South Wales, Sydney, NSW, Australia
Abstract :
Ellipses and elliptical features are evident in abundance, in a wide variety of digital images. Much of these features carry within itself useful statistical and geometrical information that can be exploited for a broad range of real-world applications. Algorithms developed of late for ellipse detection are application specific and are mainly based on traditional least-square fitting and Hough transform methods. This, in essence, is a step away from building a fully autonomous system with ellipse detection capabilities. This review attempts to redirect the research focus back towards a common goal of generating new ideas through the introduction of a modular framework.
Keywords :
Hough transforms; feature extraction; least squares approximations; Hough transform; digital images; ellipse detection methods; ellipse features; elliptical features; geometrical information; least-square fitting; real-world applications; statistical information; Detection algorithms; Feature extraction; Image edge detection; Noise; Robustness; Shape; Transforms; Hough transform; ellipse detection; feature extraction; least-square method;
Conference_Titel :
Industrial Electronics (ISIE), 2012 IEEE International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-0159-6
Electronic_ISBN :
2163-5137
DOI :
10.1109/ISIE.2012.6237243