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Journal of ZheJiang University (Engineering Science)  2023, Vol. 57 Issue (12): 2439-2447    DOI: 10.3785/j.issn.1008-973X.2023.12.011
    
Classification of microplastics and microalgae based on Mueller matrix microscopic images
Xiao-gang LU1,2(),Wei CUI2,Zhi-hang XIONG2,3,Hua-feng ZHANG1,Ran LIAO2,*()
1. School of Physics and Optoelectronic Engineering, Yangtze University, Jingzhou 434023, China
2. Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China
3. School of Physics and Optoelectronic Engineering, Foshan University, Foshan 528231, China
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Abstract  

Two categories of microplastics (polyvinyl chloride and nylon 6) and two categories of microalgae (Golenkinia and Chlamydomonas) were measured by the Mueller matrix microscope. Mueller matrix microscope was used to classify microplastics and microalgae, and the factors affecting the mothod of this classification were discussed, and the potential solutions to improve the accuracy rate of classification were proposed. Mueller matrix microscope was used to high-throughput measure the Mueller matrix of all particles within a large field of view. Then, multiple polarization parameters were calculated from the Mueller matrix, and the polarization parameters were used as characteristic values to characterize the physical properties of particles. Further, the feedforward neural network was used to classify the samples. Experimental results show that the Mueller matrix image can successfully classify microplastics and microalgae with an accuracy of more than 80%, and the feasibility of using Mueller matrix microscope to classify microplastics and microalgae in water was confirmed.



Key wordsMueller matrix microscope      Mueller matrix      microplastics      microalgae      classification of particles     
Received: 23 February 2023      Published: 27 December 2023
CLC:  O 436.3  
Fund:  国家自然科学基金资助项目(61975088, 62275141);深港联合项目(SGDX20201103095403017)
Corresponding Authors: Ran LIAO     E-mail: 2395639962@qq.com;liao.ran@sz.tsinghua.edu.cn
Cite this article:

Xiao-gang LU,Wei CUI,Zhi-hang XIONG,Hua-feng ZHANG,Ran LIAO. Classification of microplastics and microalgae based on Mueller matrix microscopic images. Journal of ZheJiang University (Engineering Science), 2023, 57(12): 2439-2447.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2023.12.011     OR     https://www.zjujournals.com/eng/Y2023/V57/I12/2439


基于缪勒矩阵显微图像的微塑料和微藻分类

使用缪勒矩阵显微镜测量2种微塑料(聚氯乙烯、尼龙6)和2种微藻(多芒藻、衣藻). 使用缪勒矩阵显微镜进行微塑料和微藻分类,讨论影响这种分类方法的多种因素,提出提高分类准确率的可能方案. 利用缪勒矩阵显微镜高通量地测量大视野范围内所有颗粒物的缪勒矩阵,由缪勒矩阵计算得到多个偏振参数,将所得偏振参数作为表征颗粒物物理性质的特征值,并进一步借助前馈神经网络实现对样品分类. 实验结果表明,利用缪勒矩阵图像数据能够成功进行微塑料和微藻分类,分类准确率均超过80%,由此验证了利用缪勒矩阵显微镜对水中微塑料和微藻进行分类的可行性.


关键词: 缪勒矩阵显微镜,  缪勒矩阵,  微塑料,  微藻,  颗粒物分类 
Fig.1 Schematic of Mueller matrix microscope
Fig.2 Images of light intensity of microplastics and microalgae
Fig.3 Schematic diagram of feedforward neural network model
Fig.4 Mueller matrix images of microplastics and microalgae
Fig.5 Confusion matrix and classification result of PVC and PA6
Fig.6 Confusion matrix and classification result of Golenkinia and Chlamydomona
Fig.7 Confusion matrix and classification result of PVC and Golenkinia
Fig.8 Confusion matrix corresponding to four classifications of four particles
Fig.9 Confusion matrix obtained after classification of two microalgae using pixel point method
Fig.10 Distribution diagram of two polarimetry basis parameters with different data processing methods
Fig.11 Images of light intensity of PVC with or without motion artifacts
运动伪影 DM DSD tM tSD bM bSD
0.628 8 0.249 3 0.273 4 0.194 3 0.791 3 0.257 2
0.027 5 0.013 0 0.027 9 0.014 8 0.992 0 0.0195
Tab.1 Mean and standard deviation of polarimetry basis parameters of PVC with or without motion artifacts
Fig.12 Distribution diagram of two polarimetry basis parameters in different focusing situations
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