Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김회율 | - |
dc.date.accessioned | 2018-06-12T00:51:31Z | - |
dc.date.available | 2018-06-12T00:51:31Z | - |
dc.date.issued | 2016-06 | - |
dc.identifier.citation | 2016년도 대한전자공학회 하계종합학술대회, page.904-907 | en_US |
dc.identifier.uri | http://www.dbpia.co.kr/Journal/ArticleDetail/NODE06724560 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/72025 | - |
dc.description.abstract | In this paper, we present a robust ego-lane detection method for various road environments. Conventional lane detection methods based on image processin are vulnerable to weather, traffic conditions and road markings whose width is similar to those of lane markings. In our proposed method, information obtained from AVM"s left and right images are utilized simultaneously with additionally processed filter response from specifically designed filter for lane detection. We confirmed experimentally that the proposed method efficiently detects lanes while rejecting other road markings. | en_US |
dc.language.iso | ko_KR | en_US |
dc.publisher | 대한전자공학회 | en_US |
dc.title | AVM 영상에서 강인한 주행차선 마킹 검출 방법 | en_US |
dc.title.alternative | Robust Ego-Lane Marking Detection Method in AVM Video | en_US |
dc.type | Article | en_US |
dc.relation.volume | p.904 | - |
dc.relation.page | 904-907 | - |
dc.contributor.googleauthor | 구근 | - |
dc.contributor.googleauthor | 조훈 | - |
dc.contributor.googleauthor | 김회율 | - |
dc.contributor.googleauthor | Gu, Geun | - |
dc.contributor.googleauthor | Jo, Hoon | - |
dc.contributor.googleauthor | Kim, Whoi-Yul | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF ELECTRONIC ENGINEERING | - |
dc.identifier.pid | wykim | - |
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