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Classification of Micromobility Vehicles in Thermal-Infrared Images Based on Combined Image and Contour Features Using Neuromorphic Processing

  • Trends of environmental awareness, combined with a focus on personal fitness and health, motivate many people to switch from cars and public transport to micromobility solutions, namely bicycles, electric bicycles, cargo bikes, or scooters. To accommodate urban planning for these changes, cities and communities need to know how many micromobility vehicles are on the road. In a previous work, we proposed a concept for a compact, mobile, and energy-efficient system to classify and count micromobility vehicles utilizing uncooled long-wave infrared (LWIR) image sensors and a neuromorphic co-processor. In this work, we elaborate on this concept by focusing on the feature extraction process with the goal to increase the classification accuracy. We demonstrate that even with a reduced feature list compared with our early concept, we manage to increase the detection precision to more than 90%. This is achieved by reducing the images of 160 × 120 pixels to only 12 × 18 pixels and combining them with contour moments to a feature vector of only 247 bytes.

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Document Type:Article
Author:Bastian Stahl, Jürgen Apfelbeck, Robert Lange
Parent Title (English):Applied Sciences
Article Number:3795
Number of pages:18
Place of publication:Basel
Publishing Institution:Hochschule Bonn-Rhein-Sieg
Date of first publication:2023/03/16
Copyright:© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Funding:This project was supported by the Federal Ministry for Economic Affairs and Energy (BMWi) on the basis of a decision by the German Bundestag. Funding code: ZF4190305GR9.
Keyword:Machine Learning; Machine vision; long-wave infrared; micromobility; neuromorphic processing; thermal imaging; traffic data; urban planning
Departments, institutes and facilities:Fachbereich Ingenieurwissenschaften und Kommunikation
Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE)
Projects:IR und ToF-Messung sowie Algorithmen zur automatischen Signalauswertung für ein System zur mobilen Fahrzeugklassifikation (RaIT-Fahrzeugklassifikation)
Dewey Decimal Classification (DDC):6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten
Entry in this database:2023/03/20
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International