Title :
Ellipse detection based on principal component analysis
Author_Institution :
Sch. of Comput. & Inf. Technol., Shan Xi Univ., Tai yuan, China
Abstract :
A method of ellipse detection and location based on principal components analysis is proposed. According to the fact that major axis of an ellipse is the direction of principal components, the data points are projected on the coordinate frame of principal axis using the principal components analysis. A new evaluation method for elliptical profile error is proposed, and the ellipse objects are recognized according to the elliptical profile error of the data points after transform. The ellipse center coordinates are optimized by Levenberg-Marquardt algorithm, and the ones of the ellipse before transform can be obtained by the anti-transform. The method simplifies the process of ellipse detection by transforming arbitrary ellipse to standard one, and the location precision is less than 0.05 pixels when the noise variance is 0.05.
Keywords :
computer vision; object recognition; principal component analysis; transforms; Levenberg-Marquardt algorithm; coordinate frame; data point projection; ellipse center coordinates; ellipse detection; ellipse location; ellipse object recognition; elliptical profile error; noise variance; principal component analysis; Covariance matrix; Fitting; Image edge detection; Noise; Pixel; Principal component analysis; Transforms; Computer vision; Ellipse recognition; PCA; Profile error;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5623040
