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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/46673
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dc.contributor.authorJun Ma-
dc.contributor.authorXunhuan Ren-
dc.contributor.authorTsviatkou, V. Y.-
dc.contributor.authorKanapelka, V. K.-
dc.coverage.spatialSwitzerland-
dc.date.accessioned2022-02-09T06:12:12Z-
dc.date.available2022-02-09T06:12:12Z-
dc.date.issued2022-
dc.identifier.citationA novel fully parallel skeletonization algorithm / Ma Jun [et al.] // Pattern Analysis and Applications. – 2022. – № 25. – P. 169–188. – DOI: 10.1007/s10044-021-01039-y.ru_RU
dc.identifier.urihttps://libeldoc.bsuir.by/handle/123456789/46673-
dc.description.abstractA Skeleton that is extracted by a skeletonization algorithm from a binary image is useful for object description, matching, recognition and compression. The parallel thinning algorithm, one of the skeletonization algorithms is well known to have computational effciency. The main contribution of this paper is that we proposed a novel fully parallel thinning algorithm based on a comprehensive investigation of the well-known Zhang-Suen (ZS)-series algorithms and the one-pass thinning algorithm (OPTA)-series algorithms, which not only has good performance in terms of (8,4) connectivity preservation and single-pixel thickness, but also has the following qualities: it is more robust to the boundary noise than the OPTA-series algorithms and it is faster than the ZS-series algorithms in terms of thinning speed, as confirmed by the experiments presented in this paper.ru_RU
dc.language.isoenru_RU
dc.publisherSpringerru_RU
dc.subjectпубликации ученыхru_RU
dc.subjectSkeletonizationru_RU
dc.subjectNoise immunityru_RU
dc.subjectFully parallelru_RU
dc.subjectConnectivityru_RU
dc.subjectThinning rateru_RU
dc.subjectThinning speedru_RU
dc.titleA novel fully parallel skeletonization algorithmru_RU
dc.typeArticleru_RU
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