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Croatian Operational Research Review, Vol.5 No.1 Ožujak 2014.

Izvorni znanstveni članak

Data clustering for circle detection

Tomislav Marošević ; Josip Juraj Strossmayer University of Osijek, Osijek, Croatia

Puni tekst: engleski, pdf (586 KB) str. 15-24 preuzimanja: 802* citiraj
APA 6th Edition
Marošević, T. (2014). Data clustering for circle detection. Croatian Operational Research Review, 5 (1), 15-24. Preuzeto s https://hrcak.srce.hr/120189
MLA 8th Edition
Marošević, Tomislav. "Data clustering for circle detection." Croatian Operational Research Review, vol. 5, br. 1, 2014, str. 15-24. https://hrcak.srce.hr/120189. Citirano 15.12.2018.
Chicago 17th Edition
Marošević, Tomislav. "Data clustering for circle detection." Croatian Operational Research Review 5, br. 1 (2014): 15-24. https://hrcak.srce.hr/120189
Harvard
Marošević, T. (2014). 'Data clustering for circle detection', Croatian Operational Research Review, 5(1), str. 15-24. Preuzeto s: https://hrcak.srce.hr/120189 (Datum pristupa: 15.12.2018.)
Vancouver
Marošević T. Data clustering for circle detection. Croatian Operational Research Review [Internet]. 2014 [pristupljeno 15.12.2018.];5(1):15-24. Dostupno na: https://hrcak.srce.hr/120189
IEEE
T. Marošević, "Data clustering for circle detection", Croatian Operational Research Review, vol.5, br. 1, str. 15-24, 2014. [Online]. Dostupno na: https://hrcak.srce.hr/120189. [Citirano: 15.12.2018.]

Sažetak
This paper considers a multiple-circle detection problem on the basis of given data. The problem is solved by application of the center-based clustering method. For the purpose of searching for a locally optimal partition modeled on the well-known k-means algorithm, the k-closest circles algorithm has been constructed. The method has been illustrated by several numerical examples.

Ključne riječi
data clustering; circle detection; k-means; locally optimal partition

Hrčak ID: 120189

URI
https://hrcak.srce.hr/120189

Posjeta: 981 *