Optical Instruments, Volume. 45, Issue 2, 8(2023)
Automatic recognition of water source microorganisms based on particle swarm optimization algorithm
Figures & Tables(13)
Fig. 2. Flow chart of the water source microorganisms recognition system
Fig. 3. Flow chart of semi-automatic microorganisms image segmentation
Fig. 5. Flow chart of establishment of the PSO-SVM recognition model
Fig. 7. Single feature recognition results of semi-automatic segmented image, automatic segmented image and evaluation standard image
Table 1. Results of parameter optimization of ISH feature
View tableView in ArticleTable 1. Results of parameter optimization of ISH feature
采样点个数 角度分区范围/（°） 特征向量维数 识别准确率/% 100 0～30, …, 150～180 6 74.16 150 0～30, ···, 150～180 6 75.25 100 0～15, ···, 165～180 12 79.41 150 0～15, ···, 165～180 12 77.72
Table 2. Results of parameter optimization of FD feature
View tableView in ArticleTable 2. Results of parameter optimization of FD feature
采样点个数 特征向量维数 识别准确率/% 50 25 83.16 100 50 86.41 150 75 88.50 200 100 86.97
Table 3. Results of parameter optimization of RI-LBP feature
View tableView in ArticleTable 3. Results of parameter optimization of RI-LBP feature
采样点个数 邻域半径/像素 特征向量维数 识别准确率/% 4 1 16 60.94 4 2 16 46.84 8 1 256 72.16 8 2 256 66.97
Table 4. Results of image evaluation of full-automatic segmentation method and semi-automatic segmentation method
View tableView in ArticleTable 4. Results of image evaluation of full-automatic segmentation method and semi-automatic segmentation method
评价指标 微生物类别 平均 月形腔轮虫 溞 猛水蚤 红虫 钩状狭甲轮虫 颤藻 未知微生物1 未知微生物2 相似度/%（全自动） 90.89 84.73 86.53 81.49 90.39 84.47 87.95 81.36 85.98 灵敏度/%（全自动） 99.42 96.10 94.00 98.14 98.25 99.19 95.94 91.27 96.54 特异度/%（全自动） 99.90 99.34 99.73 98.77 99.76 99.84 99.80 99.84 99.62 相似度/%（半自动） 94.13 91.67 90.94 94.17 95.68 87.18 89.30 84.44 90.94 灵敏度/%（半自动） 99.40 96.99 96.52 98.25 98.43 99.12 97.01 92.19 97.24 特异度/%（半自动） 99.97 99.84 99.85 99.80 99.97 99.91 99.84 99.91 99.89
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Xingang MIN, Shaoqi HUANG, Shaojie YOU, Bo DAI. Automatic recognition of water source microorganisms based on particle swarm optimization algorithm[J]. Optical Instruments, 2023, 45(2): 8
Paper Information
Category: APPLICATION TECHNOLOGY
Received: Nov. 18, 2022
Accepted: Nov. 18, 2022
Published Online: Jun. 12, 2023
The Author Email: DAI Bo (daibo@usst.edu.cn)
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