DocumentCode
1114832
Title
Curve Parametrization by Moments
Author
Popovici, Irina ; Withers, William Douglas
Author_Institution
Dept. of Math., United States Naval Acad., Annapolis, MD
Volume
31
Issue
1
fYear
2009
Firstpage
15
Lastpage
26
Abstract
We present a method for deriving a parametric description of a conic section (quadratic curve) in an image from the moments of the image with respect to several specially-constructed kernel functions. In contrast to Hough-transform-type methods, the moment approach requires no large accumulator array. Judicious implementation allows the parameters to be determined using five multiplication operations and six addition operations per pixel. The use of moments renders the calculation robust in the presence of high-frequency noise or texture and resistant to small-scale irregularities in the edge. Our method is generalizable to more complex classes of curves with more parameters as well as to surfaces in higher dimensions.
Keywords
edge detection; image texture; Hough-transform-type methods; conic section; curve parametrization; ellipse detection; high-frequency noise; image moments; parametric description; Edge and feature detection; Moments; Algorithms; Artificial Intelligence; Computer Simulation; Image Interpretation, Computer-Assisted; Models, Theoretical; Pattern Recognition, Automated;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.2008.54
Filename
4479469
Link To Document