Title :
Robust Real-Time Ellipse Detection by Direct Least-Square-Fitting
Author_Institution :
Dept. of Comput. Eng., Suzhou Vocational Univ., Suzhou
Abstract :
This paper presents a robust real-time algorithm to automatically detect and accurately locate ellipse objects in digital images. The algorithm consists of three steps. First the edge pixels are extracted using Canny edge detection algorithm and then a noise removal process is run to remove the non-ellipse edgepoints. In the second step, a direct least-square-fitting algorithm is used to calculate the ellipse parameters from each cluster of pixels. In the third step, a robust criterion is developed to identify valid ellipses. The algorithm is implemented in Visual C++ and tested on a laptop powered by an Intel Centrino Duo CPU at 1.8 GHz. The preliminary experiment shows the algorithmpsilas speed is 212 ms/images on average for image size of 640X480.
Keywords :
curve fitting; edge detection; image denoising; object detection; Canny edge detection algorithm; Intel Centrino Duo CPU; Visual C++; digital images; direct least-square-fitting algorithm; edge pixel extraction; ellipse object detection; laptop; noise removal process; Clustering algorithms; Data mining; Detection algorithms; Digital images; Filters; Gaussian noise; Image edge detection; Noise robustness; Object detection; Pixel; Circle Detection; Computer Vision; Ellipse Detection; Pattern Recognition;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.789
