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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/51997
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dc.contributor.authorYuan Liu-
dc.coverage.spatialМинскru_RU
dc.date.accessioned2023-06-14T06:18:48Z-
dc.date.available2023-06-14T06:18:48Z-
dc.date.issued2023-
dc.identifier.citationYuan Liu. Noise reduction method for skeletonized images / Yuan Liu // Информационная безопасность : сборник материалов 59-й научной конференции аспирантов, магистрантов и студентов БГУИР, Минск, 17–21 апреля 2023 г. / Белорусский государственный университет информатики и радиоэлектроники. – Минск, 2023. – С. 184–185.ru_RU
dc.identifier.urihttps://libeldoc.bsuir.by/handle/123456789/51997-
dc.description.abstractScale-space-based denoising approaches adopt scale space filters before the binarization stage to smooth the potential noise. These kinds of methods can simultaneously suppress both inner noise and border noise. Thinning framework that based on the scale space technique to automatically extract skeletons from images without manual-tuning. The proposed framework can increase the robustness of the thinning algorithm, it not only can suppress the boundary noise, but also can alleviate the inner noise. These two types of noise generally cause the appearance of the abundant of the unwanted branches in the outcome of the thinning algorithm, which arise the difficulties of the later recognition or matching process in skeleton.ru_RU
dc.language.isoenru_RU
dc.publisherБГУИРru_RU
dc.subjectматериалы конференцийru_RU
dc.subjectskeletonru_RU
dc.subjectrobustnessru_RU
dc.subjectinner noiseru_RU
dc.subjectboundary noiseru_RU
dc.titleNoise reduction method for skeletonized imagesru_RU
dc.typeArticleru_RU
Appears in Collections:Информационная безопасность : материалы 59-й научной конференции аспирантов, магистрантов и студентов (2023)

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