TY - CHAP A1 - Wohlschläger, Maximilian A1 - Khan, Yamna A1 - Leiter, Nina A1 - Versen, Martin A1 - Löder, Martin A1 - Laforsch, Christian T1 - Combining BLOB-Detection and MLP to Detect and Identify Plastics in an Environmental Matrix T2 - 2023 IEEE Sensors Applications Symposium (SAS) N2 - Environmental pollution by plastics is an increasing problem. However, state-of-the-art methods have significant disadvantages in detecting and identifying plastics directly in an environmental matrix. In this study, we propose a blob detection algorithm in combination with a neural network for fast and automated identification of plastics and non-plastics in a single fluorescence lifetime image. Therefore an artificial environmental matrix is prepared that contains soil, grass, spruce and HDPE (high density polyethylene) particles. Several FD-FLIM (frequency domain fluorescence lifetime imaging microscopy) images are taken, and the detection algorithm and the neural network are applied. We successfully demonstrated the suitability of the thresholding algorithm and the binary classification of the HDPE particles directly in the environmental matrix. KW - Fluorescence KW - Plastics KW - FD-FLIM KW - Neural networks KW - MLP KW - blob detection KW - Classification algorithms KW - Dogs KW - fluorescence lifetime KW - plastics identification KW - Soil KW - Thresholding (Imaging) Y1 - 2023 U6 - https://doi.org/10.1109/SAS58821.2023.10254171 SP - 1 EP - 5 ER -