DocumentCode :
249048
Title :
Ellipses from triangles
Author :
Cicconet, M. ; Gunsalus, K. ; Geiger, D. ; Werman, Michael
Author_Institution :
Center for Genomics & Syst. Biol., New York Univ., New York, NY, USA
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
3626
Lastpage :
3630
Abstract :
We present an ellipse finding and fitting algorithm that uses points and tangents, rather than just points, as the basic unit of information. These units are analyzed in a hierarchy: points with tangents are paired into triangles in the first layer and pairs of triangles in the second layer vote for ellipse centers. The remaining parameters are estimated via robust linear algebra: eigen-decomposition and iteratively reweighed least squares. Our method outperforms the state-of-the-art approach in synthetic images and microscopic images of cells.
Keywords :
computational geometry; curve fitting; eigenvalues and eigenfunctions; iterative methods; least squares approximations; object detection; parameter estimation; eigen-decomposition; ellipse detection; ellipse finding algorithm; ellipse fitting algorithm; image analysis; iteratively reweighed least squares; parameter estimation; pattern recognition; points-with-tangents; robust linear algebra; Databases; Educational institutions; Equations; Image edge detection; Pattern recognition; Robustness; Transforms; cell counting; ellipse detection; ellipse fitting; image analysis; pattern recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/ICIP.2014.7025736
Filename :
7025736
Link To Document :
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