Arc-based evaluation and detection of ellipses

Authors:
Yu Qiao;S. H. Ong
Affiliations:
Department of Electrical and Computer Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore and Biomedical Imaging Lab, Agency for Science, Technology ...;Department of Electrical and Computer Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore and Division of Bioengineering, National University of Sing ...
Venue:
Pattern Recognition
Year:
2007

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Abstract

We propose the use of elliptic arcs as a reliable criterion for ellipse evaluation and reconstruction. A technique based on pixel connectivity is developed for detecting the endpoints and subtended angles of elliptic arcs. Model-based distance and angular connectivity are introduced for quick and meaningful estimation of elliptic arcs. An iterative algorithm for multiple-ellipse fitting based on arc detection is presented. Experimental results confirm the robustness and accuracy of the algorithm for the fitting of multiple overlapping ellipses.