An Auto-Focus Method of Microscope for the Surface Structure of Transparent Materials under Transmission Illumination
This paper is concerned with auto-focus of microscopes for the surface structure of transparent materials under transmission illumination, where two distinct focus states appear in the focusing process and the focus position is located between the two states with the local minimum of sharpness. Plea...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/7/2487 |
| _version_ | 1827695971000123392 |
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| author | Yang Liao Yonghua Xiong Yunhong Yang |
| author_facet | Yang Liao Yonghua Xiong Yunhong Yang |
| author_sort | Yang Liao |
| collection | DOAJ |
| description | This paper is concerned with auto-focus of microscopes for the surface structure of transparent materials under transmission illumination, where two distinct focus states appear in the focusing process and the focus position is located between the two states with the local minimum of sharpness. Please note that most existing results are derived for one focus state with the global maximum value of sharpness, they cannot provide a feasible solution to this particular problem. In this paper, an auto-focus method is developed for such a specific situation with two focus states. Firstly, a focus state recognition model, which is essentially an image classification model based on a deep convolution neural network, is established to identify the focus states of the microscopy system. Then, an endpoint search algorithm which is an evolutionary algorithm based on differential evolution is designed to obtain the positions of the two endpoints of the region where the real focus position is located, by updating the parameters according to the focus states. At last, a region search algorithm is devised to locate the focus position. The experimental results show that our method can achieve auto-focus rapidly and accurately for such a specific situation with two focus states. |
| first_indexed | 2024-03-10T12:38:25Z |
| format | Article |
| id | doaj.art-2a67bdbfea45448da23e6e3c693186b1 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T12:38:25Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2a67bdbfea45448da23e6e3c693186b12023-11-21T14:05:45ZengMDPI AGSensors1424-82202021-04-01217248710.3390/s21072487An Auto-Focus Method of Microscope for the Surface Structure of Transparent Materials under Transmission IlluminationYang Liao0Yonghua Xiong1Yunhong Yang2State Key Laboratory of High Field Laser Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, ChinaSchool of Automation, China University of Geosciences, Wuhan 430074, ChinaSchool of Automation, China University of Geosciences, Wuhan 430074, ChinaThis paper is concerned with auto-focus of microscopes for the surface structure of transparent materials under transmission illumination, where two distinct focus states appear in the focusing process and the focus position is located between the two states with the local minimum of sharpness. Please note that most existing results are derived for one focus state with the global maximum value of sharpness, they cannot provide a feasible solution to this particular problem. In this paper, an auto-focus method is developed for such a specific situation with two focus states. Firstly, a focus state recognition model, which is essentially an image classification model based on a deep convolution neural network, is established to identify the focus states of the microscopy system. Then, an endpoint search algorithm which is an evolutionary algorithm based on differential evolution is designed to obtain the positions of the two endpoints of the region where the real focus position is located, by updating the parameters according to the focus states. At last, a region search algorithm is devised to locate the focus position. The experimental results show that our method can achieve auto-focus rapidly and accurately for such a specific situation with two focus states.https://www.mdpi.com/1424-8220/21/7/2487auto-focusmicroscopetransmission illuminationdeep convolution neural networkdifferential evolution |
| spellingShingle | Yang Liao Yonghua Xiong Yunhong Yang An Auto-Focus Method of Microscope for the Surface Structure of Transparent Materials under Transmission Illumination Sensors auto-focus microscope transmission illumination deep convolution neural network differential evolution |
| title | An Auto-Focus Method of Microscope for the Surface Structure of Transparent Materials under Transmission Illumination |
| title_full | An Auto-Focus Method of Microscope for the Surface Structure of Transparent Materials under Transmission Illumination |
| title_fullStr | An Auto-Focus Method of Microscope for the Surface Structure of Transparent Materials under Transmission Illumination |
| title_full_unstemmed | An Auto-Focus Method of Microscope for the Surface Structure of Transparent Materials under Transmission Illumination |
| title_short | An Auto-Focus Method of Microscope for the Surface Structure of Transparent Materials under Transmission Illumination |
| title_sort | auto focus method of microscope for the surface structure of transparent materials under transmission illumination |
| topic | auto-focus microscope transmission illumination deep convolution neural network differential evolution |
| url | https://www.mdpi.com/1424-8220/21/7/2487 |
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