The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 1821 of 1904
Back to Result List

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.

Export metadata

Additional Services

Search Google Scholar
Metadaten
Author:Maximilian Wohlschläger, Yamna Khan, Nina Leiter, Martin Versen, Martin Löder, Christian Laforsch
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