Abstract
Successful recycling of electronic waste requires accurate separation of materials such as plastics, PCBs and electronic components on PCBs (capacitors, transistors, etc.). This article therefore proposes a vision approach based on a combination of 3D and HSI data, relying on the mutual support of the datasets to compensate existing weaknesses when using single 3D- and HSI-Sensors. The combined dataset serves as a basis for the extraction of geometric and spectral features. The classification is performed and evaluated based on these extracted features which are exploited through rules. The efficiency of the proposed approach is demonstrated using real electronic waste and leads to convincing results with an overall accuracy (OA) of 98.24%. To illustrate that the addition of 3D data has added value, a comparison is also performed with an SVM classification based only on hyperspectral data.
Highlights
I3mainz, Institute for Spatial Information and Surveying Technology, Mainz University of Applied Sciences, Hubert Curien Laboratory, University Jean Monnet, 18 Rue Professeur Benoît Lauras, 42100 Saint-Etienne, France
We propose a general approach based on a combination of topological, depth and spatial information obtained from 3D sensors and physical information received from Hyperspectral Imaging (HSI)
Printed Circuit Boards (PCBs), trumspectrum for eachprovides cluster.a Since plastic objects are the usually of one(Figure material good approach to classify objectsmade in question
Summary
I3mainz, Institute for Spatial Information and Surveying Technology, Mainz University of Applied Sciences, Hubert Curien Laboratory, University Jean Monnet, 18 Rue Professeur Benoît Lauras, 42100 Saint-Etienne, France. The classification is performed and evaluated based on these extracted features which are exploited through rules. Humanity is producing more and more electronic waste. In 2019 worldwide, 53.6 million tons of electronic waste were produced. Technological innovations, short production cycles and, in particular, ever-shorter product life cycles are the reasons for this rapid increase. Due to existing toxic substances, this is harmful to the environment, but could cause serious risks for the human health. This makes recycling processes that help to achieve sustainability more important
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