Multispectral Imaging in the Recycling Process

Description

The majority of the plastic waste produced is thermally recycled, i.e. incinerated. The reason for this is that the plastics often cannot be properly identified. Multispectral imaging enables clear classification. So-called camera arrays are used for this purpose; filters in different wavelengths in the infrared range are fitted in front of the individual cameras. As plastics reflect and absorb long-wave light differently due to their different carbon chain structures, different materials appear in different colors. By creating spectral fingerprints, a neural network can then be used for unambiguous classification. In the context of multispectral imaging in the recycling process, various building blocks for this task are being investigated.

Details can be found in the following document:

Possible_Topics_for_theses

Prerequisites

Experience in programming with Python as well as image and video compression is required. Depending on the topic, additional knowledge in Deep Learning (PyTorch/TF) is needed.

Category: Bachelor Theses – Offered, Master Theses – Offered, Project Theses – Offered, Research Internships – Completed