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초록
Corrosion of steel plate is common phenomenon which results in the gradual destruction caused by a wide variety of environments. Corrosion monitoring is the tracking of the degradation progress for a long period of time. Corrosion on steel plate appears as a discoloration and any irregularities on the surface. In this study, we developed a quantitative evaluation method of the rust formed on steel plate by using k-means clustering from the corroded area in a given image. The k-means clustering for automated corrosion detection was based on the GrabCut segmentation and Gaussian mixture model(GMM). Image color of the corroded surface at cut-edge area was analyzed quantitatively based on HSV(Hue, Saturation, Value) color space.
키워드
Corrosion; GrabCut Segmentation; Gaussian Mixture Model; HSV color space; k-means clustering
- 제목
- k-means 클러스터링을 이용한 강판의 부식 이미지 모니터링
- 제목 (타언어)
- Corrosion Image Monitoring of steel plate by using k-means clustering
- 저자
- 김범수; 권재성; 최성웅; 노정필; 이경황; 양정현
- 발행일
- 2021-10
- 저널명
- 한국표면공학회지
- 권
- 54
- 호
- 5
- 페이지
- 278 ~ 284