Algae Identification Research Based on Fluorescence Spectral Imaging Technology Combined with Cluster Analysis and Principal Component Analysis

	Algae Identification Research Based on Fluorescence Spectral Imaging Technology Combined with Cluster Analysis and Principal Component Analysis
	Liang M.; Huang F. R.; He X. J.; Chen X. D.
	2014
发表期刊	Spectroscopy and Spectral Analysis
ISSN	ISBN/1000-0593
卷号	34 期号:8 页码:2132-2136
摘要	In order to explore rapid real-time algae detection methods, in the present study experiments were carried out to use fluorescence spectral imaging technology combined with a pattern recognition method for identification research of different types of algae. The fluorescence effect of algae samples is obvious during the detection. The fluorescence spectral imaging system was adopted to collect spectral images of 40 algal samples. Through image denoising, binarization processing and making sure the effective pixels, the spectral curves of each sample were drawn according to the spectral cube. The spectra in the 400 similar to 720 nm wavelength range were obtained. Then, two pattern recognition methods, i.e. hierarchical cluster analysis and principal component analysis, were used to process the spectral data. The hierarchical cluster analysis results showed that the Euclidean distance method and average weighted method were used to calculate the cluster distance between samples, and the samples could be correctly classified at a level of the distance L=2.452 or above, with an accuracy of 100%. The principal component analysis results showed that first-order derivative, second-order derivative, multiplicative scatter correction, standard normal variate and other pretreatments were carried out on raw spectral data, then principal component analysis was conducted, among which the identification effect after the second-order derivative pretreatment was shown to be the most effective, and eight types of algae samples were independently distributed in the principal component eigenspace. It was thus shown that it was feasible to use fluorescence spectral imaging technology combined with cluster analysis and principal component analysis for algae identification. The method had the characteristics of being easy to operate, fast and nondestructive.
收录类别	SCI
语种	中文
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/43718
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Liang M.,Huang F. R.,He X. J.,et al. Algae Identification Research Based on Fluorescence Spectral Imaging Technology Combined with Cluster Analysis and Principal Component Analysis[J]. Spectroscopy and Spectral Analysis,2014,34(8):2132-2136.
APA	Liang M.,Huang F. R.,He X. J.,&Chen X. D..(2014).Algae Identification Research Based on Fluorescence Spectral Imaging Technology Combined with Cluster Analysis and Principal Component Analysis.Spectroscopy and Spectral Analysis,34(8),2132-2136.
MLA	Liang M.,et al."Algae Identification Research Based on Fluorescence Spectral Imaging Technology Combined with Cluster Analysis and Principal Component Analysis".Spectroscopy and Spectral Analysis 34.8(2014):2132-2136.

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