Journal of Applied Optics, Volume. 44, Issue 3, 677(2023)
Image classification of optical element surface defects based on convolutional neural network
Figures & Tables(11)
Fig. 3. Classification flow chart of surface defect images of optical elements
Table 1. Feature extraction of surface defects
View tableView in ArticleTable 1. Feature extraction of surface defects
表面缺陷 长轴/pixel 短轴/pixel 面积/pixel2 外接矩形 面积/pixel2 长宽比 矩形度P 1 1 1 4 1 1 4 2 1 1 4 1 1 4 11 3 1 8 3 3 2.67 12 2 2 8 4 1 2 13 3 2 10 6 1.5 1.67 16 8 6 48 50 1.33 0.96 17 9 8 56 72 1.13 0.78 18 11.26 7.73 69 87.07 1.46 0.79 19 10.29 9.84 78 101.20 1.05 0.77 20 32.65 31.75 88 104.28 1.03 0.84 26 87.74 28.87 1376 2 532.95 3.1 0.54
Table 2. Comparison of network model parameters before and after improvement
View tableView in ArticleTable 2. Comparison of network model parameters before and after improvement
模型 模型总参数 Alexnet 58 271 811 Alexnet+AC 54 405 027
Table 3. Identification results of proposed network
% View tableView in ArticleTable 3. Identification results of proposed network
% 表面缺陷 Scratch Dig Noisy 准确率 100 99.75 97.4
Table 4. Model comparison experiments
View tableView in ArticleTable 4. Model comparison experiments
Model 灵敏度/% 特异性/% 精确性/% 运行时间/s VGG16 69.39 91.20 96.40 81.1 InceptionV3 71.74 92.29 97.12 79.35 ResNet50 73.87 94.17 97.32 78.56 AlexNet 77.20 92.34 97.20 18.54 Ours 89.97 96.73 99.05 18.46
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Jinyao HOU, Weiguo LIU, Shun ZHOU, Aihua GAO, Shaobo GE, Xiangguo XIAO. Image classification of optical element surface defects based on convolutional neural network[J]. Journal of Applied Optics, 2023, 44(3): 677
Paper Information
Category: Research Articles
Received: May. 30, 2022
Accepted: --
Published Online: Jun. 19, 2023
The Author Email: LIU Weiguo (wgliu@163.com)
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