Combining BLOB-Detection and MLP to Detect and Identify Plastics in an Environmental Matrix
- 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.
Author: | Maximilian Wohlschläger, Yamna Khan, Nina Leiter, Martin Versen, Martin Löder, Christian Laforsch |
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DOI: | https://doi.org/10.1109/SAS58821.2023.10254171 |
Parent Title (English): | 2023 IEEE Sensors Applications Symposium (SAS) |
Document Type: | Conference Proceeding |
Language: | English |
Publication Year: | 2023 |
Tag: | Classification algorithms; Dogs; FD-FLIM; Fluorescence; MLP; Neural networks; Plastics; Soil; Thresholding (Imaging); blob detection; fluorescence lifetime; plastics identification |
First Page: | 1 |
Last Page: | 5 |