Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 서태원 | - |
dc.date.accessioned | 2022-11-28T05:46:17Z | - |
dc.date.available | 2022-11-28T05:46:17Z | - |
dc.date.issued | 2022-02 | - |
dc.identifier.citation | SCIENTIFIC REPORTS, v. 12, NO. 1, article no. 3229, Page. 1-9 | en_US |
dc.identifier.issn | 2045-2322 | en_US |
dc.identifier.uri | https://www.nature.com/articles/s41598-022-07235-y | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/177686 | - |
dc.description.abstract | Recent years, there has been an increase in the number of high-rise buildings, and subsequently, the interest in external wall cleaning methods has similarly increased. While a number of exterior wall cleaning robots are being developed, a method to detect contaminants on the exterior walls is still required. The exteriors of most high-rise buildings today take the form of a window curtain-wall made of translucent glass. Detecting dust on translucent glass is a significant challenge. Here, we have attempted to overcome this challenge using image processing, inspired by the fact that people typically use just the 'naked eye' to recognize dust on windows. In this paper, we propose a method that detects dust through simple image processing techniques and estimates its density. This method only uses processing techniques that are not significantly restricted by global brightness and background, making it easily applicable in outdoor conditions. Dust separation was performed using a median filter, and dust density was estimated through a mean shift analysis technique. This dust detection method can perform dust separation and density estimation using only an image of the dust on a translucent window with blurry background. | en_US |
dc.description.sponsorship | This research was supported by the National Research Foundation of Korea(NRF) Grant funded by the Ministry of Science and ICT for First-Mover Program for Accelerating Disruptive Technology Development(NRF2018M3C1B9088331, NRF-2018M3C1B9088332), and Bridge Convergence R&D Program (NRF2021M3C1C3096807, NRF-2021M3C1C3096808). | en_US |
dc.language | en | en_US |
dc.publisher | NATURE RESEARCH | en_US |
dc.source | 84285_서태원.pdf | - |
dc.title | Detection method for transparent window cleaning device, image processing approach | en_US |
dc.type | Article | en_US |
dc.relation.no | 1 | - |
dc.relation.volume | 12 | - |
dc.identifier.doi | 10.1038/s41598-022-07235-y | en_US |
dc.relation.page | 1-9 | - |
dc.relation.journal | SCIENTIFIC REPORTS | - |
dc.contributor.googleauthor | Lee, Jiseok | - |
dc.contributor.googleauthor | Chae, Hobyeong | - |
dc.contributor.googleauthor | Kim, KyungMin | - |
dc.contributor.googleauthor | Kim, Hwa Soo | - |
dc.contributor.googleauthor | Seo, TaeWon | - |
dc.sector.campus | S | - |
dc.sector.daehak | 공과대학 | - |
dc.sector.department | 기계공학부 | - |
dc.identifier.pid | taewonseo | - |
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