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k-means 클러스터링을 이용한 강판의 부식 이미지 모니터링
김범수(Beomsoo Kim),권재성(Jaesung Kwon),최성웅(Sungwoong Choi),노정필(Jungpil Noh),이경황(Kyunghwang Lee),양정현(Jeonghyeon Yang) 한국표면공학회 2021 한국표면공학회지 Vol.54 No.5
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.