Acta Photonica Sinica, Volume. 51, Issue 11, 1114006(2022)
An Optical Path Automatic Alignment Method Based on Dual-target Recognition and Improved Alignment Mathematical Model
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Fig. 9. The cropping results of analog laser target and main laser target corresponding to the 8 images
Fig. 12. The software interface when the optical docking alignment is successful
Fig. 13. Optical target recognition results of the optical docking alignment process
Fig. 14. Alignment mathematical model illustration of optical docking alignment process
Table 1. Properties information statistics of each BLOB region
View tableView in ArticleTable 1. Properties information statistics of each BLOB region
No Area Coordinate X-axis direction Y-axis direction Gray integral Interval Length Interval Length 1 1 959 （185，135） ［159，210］ 52 ［111，158］ 48 392 716 2 674 （366，460） ［344，385］ 42 ［438，485］ 48 84 418 3 36 （366，443） ［363，369］ 7 ［440，445］ 6 3 466
Table 2. Object recognition results of candidate targets
View tableView in ArticleTable 2. Object recognition results of candidate targets
Order Fitting center Fitting
radius
BLOB area BLOB area inside the fitting circle Circle fitting coefficient BLOB region number Object recognition result Flag BLOB1 （184.60，134.63） 25.00 1 959 1 888 0.963 8 1 Analog laser target 1 BLOB2 （362.30，461.29） 19.25 674 485 0.719 6 4 Main laser target 2
Table 3. Analysis and comparison of the accuracy of optical target center recognition
View tableView in ArticleTable 3. Analysis and comparison of the accuracy of optical target center recognition
No. Calibration center BLOB target Circle fitting Select Center Error Center Error 1 （185.5，133.5） （184.52，136.44） -0.98，2.94 （184.60，134.63） -0.90，1.13 Circle fitting center 2 （360.0，458.5） （365.81，460.36） 5.81，1.86 （362.30，461.29） 2.30，2.79 Circle fitting center
Table 4. Statistic of target recognition of 16 alignment images
View tableView in ArticleTable 4. Statistic of target recognition of 16 alignment images
Optical path Alignment order Recognition error/pixel Recognition time/s Success flag Analog laser target Main laser target S1 1 （-0.60，-1.63） （-2.30，-4.29） 1.237 1 S1 2 （-0.38，-2.48） （-1.34，1.08） 0.656 1 S2 1 （3.20，3.06） （-1.90，-4.40） 1.125 1 S2 2 （0.99，-2.00） （-2.23，-5.03） 1.015 1 S3 1 （1.40，-2.63） （-2.30，-4.29） 0.703 1 S3 2 （1.40，-2.63） （-2.30，-4.29） 0.718 1 S4 1 （2.40，-2.63） （-2.30，-4.29） 0.797 1 S4 2 （1.40，-3.63） （-2.30，-4.29） 1.237 1 N1 1 （-0.01，-3.00） （-0.94，-0.09） 0.860 1 N1 2 （-1.01，-3.00） （-0.18，-1.29） 0.844 1 N2 1 （-1.01，-4.00） （-0.18，0.71） 0.781 1 N2 2 （0.99，-2.00） （-2.18，-1.29） 0.720 1 N3 1 （0.99，-4.00） （-1.23，-3.03） 1.281 1 N3 2 （1.40，-3.63） （-2.30，-3.29） 1.484 1 N4 1 （0.40，-1.60） （-2.30，-1.29） 1.062 1 N4 2 （2.40，-1.63） （-3.30，-2.29） 0.720 1
Table 5. Time analysis of object recognition algorithm
View tableView in ArticleTable 5. Time analysis of object recognition algorithm
No BLOB
number
Dilate time/s Edge detection/s Total time/s Dilate once Dilate 5 times Detection region/original image size Original time Improved time Img1 3 0.359 2.781 0.95% 0.469 0.094 1.237 Img2 17 0.279 2.906 6.02% 0.485 0.187 0.656 Img3 3 0.297 1.312 0.95% 1.500 0.204 1.062 Img4 5 0.296 1.360 3.13% 1.000 0.047 0.781 Img5 2 0.313 1.375 3.46% 0.422 0.032 1.125
Table 6. Statistics of optical docking alignment control devices
View tableView in ArticleTable 6. Statistics of optical docking alignment control devices
No. Name Classification Quantity Explanation 1 Laser beam Large science device 8 8-path laser beams 2 Laser source Optical device 2 Analog laser source and main laser source 3 Alignment CCD Measuring instrument 8 Capture the image of optical docking alignment process 4 BM6 2D motorized frame Sports device 16 Each path beam needs a X-direction motor and a Y-direction motor 5 Science CCD Measuring instrument 16 Capture the near-field image of preamplifier and main amplifier 6 Energy meter Measuring instrument 24 Measure preamplifier，main amplifier and target area energy 7 Oscilloscope Measuring instrument 2 One for preamplifier and main amplifier，the other for target area
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Jiafu GUO, Zhengzhou WANG, Yaxuan DUAN, Li WANG, Zhengmao XIE. An Optical Path Automatic Alignment Method Based on Dual-target Recognition and Improved Alignment Mathematical Model[J]. Acta Photonica Sinica, 2022, 51(11): 1114006
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Received: Apr. 17, 2022
Accepted: Jun. 5, 2022
Published Online: Dec. 13, 2022
The Author Email: WANG Zhengzhou (azhou_china@126.com)
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