DocumentCode :
1533493
Title :
A method to detect and characterize ellipses using the Hough transform
Author :
Bennett, Nick ; Burridge, Robert ; Saito, Naoki
Author_Institution :
Schlumberger-Doll Res., Ridgefield, CT, USA
Volume :
21
Issue :
7
fYear :
1999
fDate :
7/1/1999 12:00:00 AM
Firstpage :
652
Lastpage :
657
Abstract :
We describe a new technique for detecting and characterizing ellipsoidal shapes automatically from any type of image. This technique is a single pass algorithm which can extract any group of ellipse parameters or characteristics which can be computed from those parameters without having to detect all five parameters for each ellipsoidal shape. Moreover, the method can explicitly incorporate any a priori knowledge the user may have concerning ellipse parameters. The method is based on techniques from projective geometry and on the Hough transform. This technique can significantly reduce interpretation and computation time by automatically extracting only those features or geometric parameters of interest from images and making exact use of a priori information
Keywords :
Hough transforms; computational geometry; computer vision; edge detection; feature extraction; object recognition; parameter estimation; Hough transform; computer vision; edge detection; ellipses; feature extraction; parameter estimation; projective geometry; shape recognition; Computational geometry; Computational modeling; Computer vision; Data mining; Equations; Feature extraction; Image edge detection; Image sampling; Parameter estimation; Shape;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.777377
Filename :
777377
Link To Document :
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