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dc.date2022-12
dc.date.accessioned2025-08-27T05:21:14Z-
dc.date.available2025-08-27T05:21:14Z-
dc.date.issued2022-12
dc.identifier.identifierDspace\SGAU\20231226\107748
dc.identifier.citationSeredin OS, Kushnir OA, Fedotova SA. Comparative analysis of reflection symmetry detection methods in binary raster images with skeletal and contour representations. Computer Optics 2022; 46(6): 921-928. DOI: 10.18287/2412-6179-CO-1115.
dc.identifier.urihttps://dx.doi.org/10.18287/2412-6179-CO-1115
dc.identifier.urihttp://repo.ssau.ru/jspui/handle/123456789/23063-
dc.description.abstractThe study is a comparative analysis of two fast reflection symmetry axis detection methods: an algorithm to refine the symmetry axis found with a chain of skeletal primitives and a boundary method based on the Fourier descriptor. We tested the algorithms with binary raster images of plant leaves (FLAVIA database). The symmetry axis detection quality and performance indicate that both methods can be used to solve applied problems. Neither method demonstrated any significant advantage in terms of accuracy or performance. It is advisable to integrate both methods for solving real-life problems.
dc.description.sponsorshipThis study was supported by the Russian Science Foundation, Grant No. 22-21-00575, https://rscf.ru/project/22-21-00575/.
dc.languageen
dc.publisherСамарский национальный исследовательский университет
dc.relation.ispartofseries46;6
dc.titleComparative analysis of reflection symmetry detection methods in binary raster images with skeletal and contour representations
dc.typeArticle
dc.identifier.scsti29.31.15, 29.33.43, 20.53.23
local.identifier.oldurihttp://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Comparative-analysis-of-reflection-symmetry-detection-methods-in-binary-raster-images-with-skeletal-and-contour-representations-107748
local.identifier.oldurihttp://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Comparative-analysis-of-reflection-symmetry-detection-methods-in-binary-raster-images-with-skeletal-and-contour-representations-107748
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