A Method of Backscattering Micro-Spectrum Classification Based on Principal Component Analysis and Fuzzy Cluster Analysis

Wang Cheng; Jiao Tong; Lu Yufei; Xu Kang; Li Sen; Liu Jing; Zhang Dawei

doi:10.3788/CJL202047.0207030

Chinese Journal of Lasers, Volume. 47, Issue 2, 207030(2020)

A Method of Backscattering Micro-Spectrum Classification Based on Principal Component Analysis and Fuzzy Cluster Analysis

Wang Cheng^1、*, Jiao Tong¹, Lu Yufei², Xu Kang¹, Li Sen³, Liu Jing³, and Zhang Dawei⁴

Author Affiliations

¹Institute of Biomedical Optics and Optometry, Key Lab of Medical Optical Technology and Instruments, Ministry of Education, University of Shanghai for Science and Technology, Shanghai 200093, China

²Department of Nephrology, Zhongshan Hospital Affiliated to Shanghai Medical College of Fudan University, Shanghai Institute of Nephrology and Dialysis, Shanghai Key Laboratory of Kidney Disease and Blood Purification, Shanghai Priority Clinical Medical Center of Kidney Disease, Shanghai 200030, China

³Institute of Food Microbiology, School of Medical Instruments and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

⁴Engineering Research Center of Optical Instrument and System, Ministry of Education, Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai 200093, China

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Figures & Tables(7)

Fig. 1. Schematic of FCBS

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Fig. 2. Average spectral curves of three bacteria

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Fig. 3. Scatter diagram of principal component analysis

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Table 1. Characteristic values, contribution rates and cumulative contribution rates of the top 10 principal components

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Table 1. Characteristic values, contribution rates and cumulative contribution rates of the top 10 principal components

Principalcomponent	Eigenvalue	Contributionrate /%	Cumulativecontribution rate/%
PC1	365.68	51.22	51.22
PC2	153.48	21.50	72.71
PC3	34.85	4.88	77.59
PC4	11.86	1.66	79.25
PC5	8.23	1.15	80.41
PC6	3.88	0.54	80.95
PC7	2.75	0.39	81.34
PC8	2.58	0.36	81.70
PC9	2.49	0.35	82.05
PC10	2.45	0.34	82.39

Table 2. Sample centers of three categories of bacteria

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Table 2. Sample centers of three categories of bacteria

Category	PC1	PC2	PC3	PC4	PC5
Salmonella enteritidis	-21.5369	9.490555	-1.04738	-0.11298	0.61074
Escherichia coli	-2.00409	-16.7138	0.859515	0.530634	-0.38007
Salmonella typhimurium	24.69104	7.681297	-1.05527	0.375939	-0.34884

Table 3. Degree matrix of membership

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Table 3. Degree matrix of membership

Number	Category 1	Category 2	Category 3
…	…	…	…
4	0.027233	0.958289	0.014478
5	0.018191	0.972088	0.009721
6	0.036999	0.942856	0.020145
7	0.027408	0.958441	0.014151
8	0.017165	0.973906	0.008929
…	…	…	…
63	0.954039	0.025693	0.020268
64	0.977193	0.012438	0.010369
65	0.970293	0.016502	0.013205
66	0.981302	0.010118	0.008579
67	0.992609	0.00412	0.003271
…	…	…	…
112	0.028499	0.020526	0.950975
113	0.041780	0.031539	0.926681
114	0.027153	0.016674	0.956173
115	0.105551	0.093608	0.800841
116	0.008976	0.005843	0.985182
…	…	…	…

Table 4. Discriminant analysis results of three kinds of bacteria

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Table 4. Discriminant analysis results of three kinds of bacteria

Category	Discriminant analysis result
Category	Category 1	Category 2	Category 3
Salmonella enteritidis(50 groups )	0	50	0
Escherichia coli(50 groups)	50	0	0
Salmonella typhimurium(50 groups)	0	0	50
Discriminantaccuracy /%	100	100	100

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Wang Cheng, Jiao Tong, Lu Yufei, Xu Kang, Li Sen, Liu Jing, Zhang Dawei. A Method of Backscattering Micro-Spectrum Classification Based on Principal Component Analysis and Fuzzy Cluster Analysis[J]. Chinese Journal of Lasers, 2020, 47(2): 207030

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Paper Information

Category: biomedical photonics and laser medicine

Received: Oct. 8, 2019

Accepted: --

Published Online: Feb. 21, 2020

The Author Email: Cheng Wang (shhwangcheng@163.com)

DOI:10.3788/CJL202047.0207030

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology