한국가시화정보학회지 (Journal of the Korean Society of Visualization)

  • 제19권1호
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  • Pages.68-73
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  • 2021
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  • 1598-8430(pISSN)
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  • 2093-808X(eISSN)
한국가시화정보학회 (The Korean Society of Visualization)
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K-겹 교차 검증과 서포트 벡터 머신을 이용한 고무 오링결함 검출 시스템

Rubber O-ring defect detection system using K-fold cross validation and support vector machine

  • 투고 : 2021.03.10
  • 심사 : 2021.04.08
  • 발행 : 2021.04.30
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초록

In this study, the detection of rubber o-ring defects was carried out using k-fold cross validation and Support Vector Machine (SVM) algorithm. The data process was carried out in 3 steps. First, we proceeded with a frame alignment to eliminate unnecessary regions in the learning and secondly, we applied gray-scale changes for computational reduction. Finally, data processing was carried out using image augmentation to prevent data overfitting. After processing data, SVM algorithm was used to obtain normal and defect detection accuracy. In addition, we applied the SVM algorithm through the k-fold cross validation method to compare the classification accuracy. As a result, we obtain results that show better performance by applying the k-fold cross validation method.

키워드

과제정보

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2020R1A5A8018822).

참고문헌

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