Title :
A real-time ellipse detection based on edge grouping
Author :
Nguyen, Thanh Minh ; Ahuja, Siddhant ; Wu, Q. M Jonathan
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Windsor, Windsor, ON, Canada
Abstract :
In this paper, we present a efficient algorithm for real-time ellipse detection. Unlike Hough transform algorithm that is computationally intense and requires a higher dimensional parameter space, our proposed method reduces the computational complexity significantly, and accurately detects ellipses in realtime. We present a new method of detecting arc-segments from the image, based on the properties of ellipse. We then group the arc-segments into elliptical arcs in order to estimate the parameters of the ellipse, which are calculated using the least-square method. Our method has been tested and implemented on synthetic and real-world images containing both complete and incomplete ellipses. The performance is compared to existing ellipse detection algorithms, demonstrating the robustness, accuracy and effectiveness of our algorithm.
Keywords :
Hough transforms; computational complexity; edge detection; least mean squares methods; parameter estimation; Hough transform algorithm; arc-segment detection; computational complexity; edge grouping; ellipse detection algorithms; least-square method; parameter estimation; real-time ellipse detection; Cancer detection; Cybernetics; Detection algorithms; Image edge detection; Joining processes; Least squares methods; Noise robustness; Parameter estimation; Real time systems; Vehicle detection; Ellipse detection; curve segments; edge grouping; real-time;
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
DOI :
10.1109/ICSMC.2009.5346226