In this work, multispectral imaging (MSI) is introduced as an innovative, practical, and non-invasive solution capable of identifying and detecting (micro)plastics. MSI holds significant appeal for industry due to its flexibility, ease of implementation, and portability. The integration of MSI with Principal Components Analysis (PCA) enables precise identification of different plastics and differentiation of microplastics within mixtures. The technique successfully identifies and quantifies the pure spectral response (endmembers) of each microplastic in every pixel of the original image. As a result, the model excels in distinguishing specific plastic materials from their surrounding backgrounds. This novel approach facilitates the identification of randomly dispersed microplastics in water.