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영상분할법을 이용한 강판상의 부식 감지
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 김범수 | - |
| dc.contributor.author | 김연원 | - |
| dc.contributor.author | 양정현 | - |
| dc.date.accessioned | 2022-12-26T11:45:55Z | - |
| dc.date.available | 2022-12-26T11:45:55Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.issn | 1225-8024 | - |
| dc.identifier.issn | 2288-8403 | - |
| dc.identifier.uri | https://scholarworks.gnu.ac.kr/handle/sw.gnu/5372 | - |
| dc.description.abstract | The visual inspection method is widely used for corrosion damage analysis of steel plate due to the cost-efficient, fast and reasonably accurate results. However, visual inspection of corrosion deteriorated degree has a problem that the reliability of results differs depending on the inspector’s individual knowledge and experience. In this study, we evaluated the degree of corrosion from a given image by using image segmentation method based on the grabcut and HSV(Hue, Saturation, Value) color image processing techniques for the development of an automatic inspection tool. The code written in Python based OpenCV-python libraries was used to categorize the images. | - |
| dc.format.extent | 6 | - |
| dc.language | 한국어 | - |
| dc.language.iso | KOR | - |
| dc.publisher | 한국표면공학회 | - |
| dc.title | 영상분할법을 이용한 강판상의 부식 감지 | - |
| dc.title.alternative | Detection of corrosion on steel plate by using Image Segmentation Method | - |
| dc.type | Article | - |
| dc.publisher.location | 대한민국 | - |
| dc.identifier.bibliographicCitation | 한국표면공학회지, v.54, no.2, pp 84 - 89 | - |
| dc.citation.title | 한국표면공학회지 | - |
| dc.citation.volume | 54 | - |
| dc.citation.number | 2 | - |
| dc.citation.startPage | 84 | - |
| dc.citation.endPage | 89 | - |
| dc.identifier.kciid | ART002714392 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.subject.keywordAuthor | Image Segmentation | - |
| dc.subject.keywordAuthor | Corrosion | - |
| dc.subject.keywordAuthor | Grabcut | - |
| dc.subject.keywordAuthor | HSV color | - |
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