TY - GEN
T1 - An Image Quality Assessment Method for Surface Defect Inspection
AU - Lin, Hsien I.
AU - Lin, Po Yi
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - The primary goal in developing an automatic defect inspection system is to obtain good-quality images. High image quality helps image detection methods extract defect features. Thus, this study proposes a comprehensive evaluation index to evaluate the image quality of image datasets for training defect detection models. Obtained images can be evaluated by the proposed index immediately as long as the lighting configuration is changed. The index consists of three parts: the image visibility, the dispersion of the image visibility of the dataset, and the image overexposure. Experiments validated that the comprehensive evaluation index was more consistent with the F2-score than the defect visibility using a YOLO defect detection model.
AB - The primary goal in developing an automatic defect inspection system is to obtain good-quality images. High image quality helps image detection methods extract defect features. Thus, this study proposes a comprehensive evaluation index to evaluate the image quality of image datasets for training defect detection models. Obtained images can be evaluated by the proposed index immediately as long as the lighting configuration is changed. The index consists of three parts: the image visibility, the dispersion of the image visibility of the dataset, and the image overexposure. Experiments validated that the comprehensive evaluation index was more consistent with the F2-score than the defect visibility using a YOLO defect detection model.
KW - Automatic defect inspection
KW - YOLO defect detection model
KW - comprehensive evaluation index
UR - http://www.scopus.com/inward/record.url?scp=85092270397&partnerID=8YFLogxK
U2 - 10.1109/AITEST49225.2020.00008
DO - 10.1109/AITEST49225.2020.00008
M3 - Conference contribution
AN - SCOPUS:85092270397
T3 - Proceedings - 2020 IEEE International Conference on Artificial Intelligence Testing, AITest 2020
SP - 1
EP - 6
BT - Proceedings - 2020 IEEE International Conference on Artificial Intelligence Testing, AITest 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Artificial Intelligence Testing, AITest 2020
Y2 - 3 August 2020 through 6 August 2020
ER -