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Automatic Particle Measurement Method Based on Circle Fitting Aided Recognition Algorithm
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摘要: 球形颗粒的粒度粒形通常采用显微成像和图像分析法进行测量，需由人工处理每个颗粒图像，操作耗时且会引入人为误差。提出了基于圆形拟合辅助识别算法的颗粒粒度粒形自动测量方法，采用圆形拟合预先识别显微图像中的单个颗粒，并以拟合结果为指导优化颗粒边缘识别，从而实现球形颗粒的粒度粒形自动测量。与人工处理结果相比，自动测量在确保测量结果一致性的同时极大提高了测量速度与重复性。Abstract: The microscope imaging and image analysis method was commonly used for the size and geometry measurement of spherical particles. As manual processing for particle images were required, the measurement procedure was time-consuming, and extra uncertainties were introduced. To solve this problem, the automatic particle measurement method based on circle fitting aided recognition algorithm was developed. The automatic particle size and geometry analyses were realized by using circle fitting aided single-particle recognition, followed by the optimization of edge recognition. Comparing with the manual method, the automatic method greatly speeds up the image processing procedure with better repeatability.
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Key words:
- particle measurement /
- particle size /
- image processing /
- circle fitting /
- particle edge recognition
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图 1 颗粒显微成像和图像分析法流程
Figure 1. Flow chart of particle microscopic imaging and image analysis
图 2 阈值法颗粒图像二值化与人工精调处理过程
Figure 2. Thresholding particle image binarization and manual fine-tuning process
图 3 颗粒粒度粒型自动处理方法流程
Figure 3. Automatic processing method and process of particle size and shape
图 4 标准物质的扫描电子显微镜图像与自动识别结果
Figure 4. Scanning electron microscope images and automatic recognition results of reference materials
表 1 标准物质物理直径测量结果
Table 1. Measurement results of physical diameter of reference materials
标准物
质编号证书
值/μm人工测量
结果/μm自动测量
结果/μmGBW 13642 1.515 ± 0.040 1.481 1.497 GBW 13649 4.157 ± 0.072 4.173 4.166 
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表 2 标准物质（GBW13642）物理直径测量重复性
Table 2. Repeatability of physical diameter measurement of reference material (GBW13642)
物理直径均值/μm 标准偏差/μm 操作人员1 1.488 0.004 操作人员2 1.493 0.003 自动方法 1.498 0
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表 3 标准物质（GBW13649）物理直径测量重复性
Table 3. Repeatability of physical diameter measurement of reference material (GBW13649)
物理直径均值/μm 标准偏差/μm 操作人员1 4.169 0.006 操作人员2 4.174 0.005 自动方法 4.161 0
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[1] 邢化朝, 刘俊杰, 许潇, 等. 纳米颗粒的粒径测量方法[J]. 中国粉体技术, 2016, 22(5): 54-57. [2] 张文阁, 刘巍, 许潇, 等. PM2.5监测仪检测用国家一级标准物质的研制[J]. 计量学报, 2019, 40(1): 159-163. doi: 10.3969/j.issn.1000-1158.2019.z1.34 [3] JIANG X, ZHANG R J, NIE S D. Image segmentation based on level set method[J]. Physics Procedia, 2013(33): 840-845. [4] International Organization for Standardization. Particle size analysis — Image analysis methods — Part 1: Static image analysis methods: ISO 13322-1: 2014[S]. Geneva: International Organization for Standardization, 2014. [5] 牛利, 尹唱唱, 刘喜禄, 等. 一种基于迭代直径圆检测的大气颗粒物图像分割方法[J]. 中国科技论文, 2018, 13(20): 2330-2336. doi: 10.3969/j.issn.2095-2783.2018.20.008 [6] LIU D, WANG Y T, TANG Z, et al. A robust circle detection algorithm based on top-down least-square fitter analysis[J]. Computers & Electrical Engineering, 2014, 40(4): 1415-1428. [7] MARCO T D, CAZZATO D, LEO M, et al. Randomized circle detection with isophotes curvature analysis[J]. Pattern Recognition, 2015, 48(2): 411-421. doi: 10.1016/j.patcog.2014.08.007 [8] ALOMARI Y M, ABDULLAH S N H S, AZMA R Z, et al. Automatic detection and quantification of WBCs and RBCs using iterative structured circle detection algorithm[J]. Computational and Mathematical Methods in Medicine, 2014, 10(2): 1-17. [9] XU X, LI T, XU Z X, et al. Automatic enumeration of gold nanomaterials at the single-particle level[J]. Analytical Chemistry, 2015, 87(5): 2576-2581. doi: 10.1021/ac503756f [10] LI T, XU X, ZHANG G Q, et al. Nonamplification sandwich assay platform for sensitive nucleic acid detection based on AuNPs enumeration with the dark-field microscope[J]. Analytical Chemistry, 2016, 88(8): 4188-4191. doi: 10.1021/acs.analchem.6b00535 [11] PEI X J, YIN H Y, LAI T C, et al. Multiplexed detection of attomoles of nucleic acids using fluorescent nanoparticle counting platform[J]. Analytical Chemistry, 2018, 90(2): 1376-1383. doi: 10.1021/acs.analchem.7b04551 [12] JOHN C. A computational approach to edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, PAMI-8(6): 679-698. doi: 10.1109/TPAMI.1986.4767851 [13] RICHARD O D, PETER E H. Use of the Hough transformation to detect lines and curves in pictures[J]. Communications of the ACM, 1972, 15(1): 11-15. doi: 10.1145/361237.361242 -
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