- 영상처리와 SVM을 이용한 Billet의 스크래치 결함 분류
- ㆍ 저자명
- 이상준,김상우,Lee. Sang Jun,Kim. Sang Woo
- ㆍ 간행물명
- 제어·로봇·시스템학회 논문지
- ㆍ 권/호정보
- 2013년|19권 3호|pp.256-261 (6 pages)
- ㆍ 발행정보
- 제어로봇시스템학회
- ㆍ 파일정보
- 정기간행물| PDF텍스트
- ㆍ 주제분야
- 기타
In the steel manufacturing area, researches for defect inspection receive a big attention for quality control. This paper proposes an algorithm to detect a scratch defect on steel billets. This algorithm takes ROIs (Regions of Interest), and extracts 11 features which represent properties of defect on a ROI. SVM (Support Vector Machine) is used to classify defect and normal ROIs. The algorithm classifies a frame image of a Billet as a defect image if there is one or more defect ROIs. In the experiments, the proposed algorithm had reliable classifying accuracy.