Automatic Particle Measurement Method Based on Circle Fitting Aided Recognition Algorithm

XU Xiao; ZHANG Wenge; CHI Shunxin

doi:10.3969/j.issn.2096-9015.2021.03.03

Volume 65 Issue 3

Mar. 2021

Turn off MathJax

Article Contents

Article Navigation > Metrology Science and Technology > 2021 > 65(3): 15-18

XU Xiao, ZHANG Wenge, CHI Shunxin. Automatic Particle Measurement Method Based on Circle Fitting Aided Recognition Algorithm[J]. Metrology Science and Technology, 2021, 65(3): 15-18. doi: 10.3969/j.issn.2096-9015.2021.03.03

Citation:

XU Xiao, ZHANG Wenge, CHI Shunxin. Automatic Particle Measurement Method Based on Circle Fitting Aided Recognition Algorithm[J]. Metrology Science and Technology, 2021, 65(3): 15-18. doi: 10.3969/j.issn.2096-9015.2021.03.03

Citation:

PDF( 563 KB)

Automatic Particle Measurement Method Based on Circle Fitting Aided Recognition Algorithm

doi: 10.3969/j.issn.2096-9015.2021.03.03

National Institute of Metrology, Beijing 100029, China

Available Online: 2021-04-13
Publish Date: 2021-03-12

Abstract

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.
- particle measurement,
- particle size,
- image processing,
- circle fitting,
- particle edge recognition

FullText(HTML)

References(13)

References

[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. PM_2.5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