A fast and efficient method for solving the multiple line detection problem
Rudolf Scitovski
orcid.org/0000-0002-7386-5991
; Department of Mathematics, University of Osijek, 31 000 Osijek, Croatia
Una Radojičić
; Department of Mathematics, University of Osijek, 31 000 Osijek, Croatia
Kristian Sabo
; Department of Mathematics, University of Osijek, 31 000 Osijek, Croatia
APA 6th Edition Scitovski, R., Radojičić, U. i Sabo, K. (2019). A fast and efficient method for solving the multiple line detection problem. Rad Hrvatske akademije znanosti i umjetnosti, (538=23), 123-140. https://doi.org/10.21857/yvjrdcqq8y
MLA 8th Edition Scitovski, Rudolf, et al. "A fast and efficient method for solving the multiple line detection problem." Rad Hrvatske akademije znanosti i umjetnosti, vol. , br. 538=23, 2019, str. 123-140. https://doi.org/10.21857/yvjrdcqq8y. Citirano 17.01.2021.
Chicago 17th Edition Scitovski, Rudolf, Una Radojičić i Kristian Sabo. "A fast and efficient method for solving the multiple line detection problem." Rad Hrvatske akademije znanosti i umjetnosti , br. 538=23 (2019): 123-140. https://doi.org/10.21857/yvjrdcqq8y
Harvard Scitovski, R., Radojičić, U., i Sabo, K. (2019). 'A fast and efficient method for solving the multiple line detection problem', Rad Hrvatske akademije znanosti i umjetnosti, (538=23), str. 123-140. https://doi.org/10.21857/yvjrdcqq8y
Vancouver Scitovski R, Radojičić U, Sabo K. A fast and efficient method for solving the multiple line detection problem. Rad Hrvatske akademije znanosti i umjetnosti [Internet]. 2019 [pristupljeno 17.01.2021.];(538=23):123-140. https://doi.org/10.21857/yvjrdcqq8y
IEEE R. Scitovski, U. Radojičić i K. Sabo, "A fast and efficient method for solving the multiple line detection problem", Rad Hrvatske akademije znanosti i umjetnosti, vol., br. 538=23, str. 123-140, 2019. [Online]. https://doi.org/10.21857/yvjrdcqq8y
Sažetak In this paper, we consider the multiple line detection problem on the basis of a data points set coming from a number of lines not known in advance. A new and efficient method is proposed, which is based upon center-based clustering, and it solves this problem quickly and precisely. The method has been tested on 100 randomly generated data sets. In comparison to the incremental algorithm, the method gives significantly better results. Also, in order to identify a partition with the most appropriate number of clusters, a new index has been proposed for the case of a cluster whose lines are cluster-centers. The index can also be generalized for other geometrical objects.