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Multispectral Imaging as a Tool for Identifying Spectral Responses of Different Plastic Materials
Summary
Researchers applied multispectral imaging integrated with principal component analysis to identify and distinguish different plastic materials and microplastics within mixtures, extracting pure spectral end members for each plastic type from every pixel of the image. The method successfully identified randomly dispersed microplastics in water, offering a portable and non-invasive alternative to conventional plastic identification techniques.
Multispectral Imaging (MSI) is presented as an innovative, practical and non-invasive solution for the identification and detection of (micro)plastics. MSI is attractive to industry because of its flexibility, ease of implementation and portability. The integration of MSI with Principal Component Analysis (PCA) allows precise identification of different plastics and differentiation of microplastics within mixtures. The technique successfully identifies and quantifies the pure spectral response (end members) of each microplastic in each pixel of the original image. As a result, the model excels at distinguishing specific plastic materials from their surrounding backgrounds. This novel approach facilitates the identification of randomly dispersed micro plastics in water.