Detecting ellipses of limited eccentricity in images with high noise levels

Autor(en): Kasemir, KU
Betzler, K
Stichwörter: Computer Science; Computer Science, Artificial Intelligence; Computer Science, Software Engineering; Computer Science, Theory & Methods; differential evolution; ellipse detection; Engineering; Engineering, Electrical & Electronic; HOUGH TRANSFORM; Optics
Erscheinungsdatum: 2003
Herausgeber: ELSEVIER SCIENCE BV
Journal: IMAGE AND VISION COMPUTING
Volumen: 21
Ausgabe: 2
Startseite: 221
Seitenende: 227
Zusammenfassung: 
We present a newly developed algorithm for the detection of elliptical shapes in images in the presence of high noise levels. The algorithm combines a modified version of the Hough transform with a genetic algorithm, namely Differential Evolution. Suggestions for a parallel implementation are given. In our implementation the algorithm is restricted due to the technical problem to be solved, yet it can be easily generalized to arbitrary ellipse detection. (C) 2003 Elsevier Science B.V. All rights reserved.
ISSN: 02628856
DOI: 10.1016/S0262-8856(02)00155-5

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