DC Field | Value | Language |
dc.contributor.author | Yuan Liu | - |
dc.coverage.spatial | Минск | ru_RU |
dc.date.accessioned | 2023-06-14T06:18:48Z | - |
dc.date.available | 2023-06-14T06:18:48Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Yuan 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.uri | https://libeldoc.bsuir.by/handle/123456789/51997 | - |
dc.description.abstract | Scale-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.iso | en | ru_RU |
dc.publisher | БГУИР | ru_RU |
dc.subject | материалы конференций | ru_RU |
dc.subject | skeleton | ru_RU |
dc.subject | robustness | ru_RU |
dc.subject | inner noise | ru_RU |
dc.subject | boundary noise | ru_RU |
dc.title | Noise reduction method for skeletonized images | ru_RU |
dc.type | Article | ru_RU |
Appears in Collections: | Информационная безопасность : материалы 59-й научной конференции аспирантов, магистрантов и студентов (2023)
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