A review of optical component defect detection based on deep learning

Ali Shan; Jishi Zheng; Feifan Lv; Linghua Kong; Dingrong Yi; Chenyu Guo; Yan Wang

doi:10.1117/12.3049638

8 November 2024 A review of optical component defect detection based on deep learning

Ali Shan, Jishi Zheng, Feifan Lv, Linghua Kong, Dingrong Yi, Chenyu Guo, Yan Wang

Author Affiliations +

Proceedings Volume 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024); 134161E (2024) https://doi.org/10.1117/12.3049638
Event: 2024 4th International Conference on Advanced Algorithms and Neural Networks, 2024, Qingdao, China

Abstract

For the past few years, detecting object surface defects using deep learning has become an important tool in industry and a major research area for researchers involved. There is a wide variety of articles on object surface defect detection, this paper will help readers to better specialize in defect detection of optical components. This review focuses on the needs of optical component detection in industry, the acquisition of datasets for different kinds of special optical component parts, and focuses on the use of deep learning algorithms in the domain of optical component surface defect detection, introducing convolutional neural networks, attention mechanisms, self-encoders, and adversarial generative networks, and their applications in optical component defect detection, and listing the performance ratios of the pixel-level models for automated optical detection pixel-level model performance ratios. This review will give the reader a quick and basic understanding of optical component defect detection and the deep learning algorithms used today.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ali Shan, Jishi Zheng, Feifan Lv, Linghua Kong, Dingrong Yi, Chenyu Guo, and Yan Wang "A review of optical component defect detection based on deep learning", Proc. SPIE 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), 134161E (8 November 2024); https://doi.org/10.1117/12.3049638

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KEYWORDS

Defect detection

Optical components

Deep learning

Data modeling

Optical surfaces

Performance modeling

Image segmentation

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