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Macroscopic samples of household waste were experimentally characterized by a sequence of images, taken in four distinct wavelength regions by NIRIS. The obtained three-dimensional stack of images serves as individual fingerprint for each sample. A rapid data compression, followed by an abstract factor rotation of this stack into a spectroscopically meaningful intermediate four-element vector by a method called multivariate image rank analysis (MIRA), finally provided a single number. This number serves as decision limit for detection of plastics among nonplastic waste. The MIRA results are independent of sample size and sample position within the camera image. They are sensitive to only the type of sample material. MIRA was also found to be robust against image errors such as shadow or slight sample replacements between measurements.

analytical chemistry

Identification of Plastics among Nonplastics in Mixed Waste by Remote Sensing Near-Infrared Imaging Spectroscopy. 2. Multivariate Image Rank Analysis for Rapid Classification