David Švorc

This article presents the use of the combination of the object detection method and feature detector in an infrared video on traffic infrastructure and in tunnels. The theme of the paper is the validation of vehicle detection and its classification using infrared video streams. In addition, the article focuses on the use of a feature detector and object detection to distinguish between vehicles with electric and combustion motors. The method suggests the use of a low-resolution thermal camera as an inexpensive extension of installed thermal camera technologies. The developed system has been verified for the applicability of vehicle detection and classification using object detection methods and their application in transport infrastructure and tunnels. It also presents a method for distinguishing propulsion units into electric and internal combustion; both systems’ conclusions are then statistically verified. The application of the system is evident in regional traffic management systems, including safety applications for traffic control in tunnels. Categorizing vehicles provides valuable information for higher levels of traffic management, toll systems, and municipal database systems, as well as for a preventive system for estimating vehicle conditions and their potential of fire in tunnels.

The main goal of this paper is to present new possibilities for the detection and recognition of different categories of electric and conventional (equipped with combustion engines) vehicles using a thermal video camera. The paper presents a draft of a possible detection and classification system of vehicle propulsion systems working with thermal analyses. The differences in thermal features of different vehicle categories were found out and statistically proved. The thermal images were obtained using an infrared thermography camera. They were utilized to design a database of vehicle class images of passenger vehicles (PVs), vans, and buses. The results confirmed the hypothesis that infrared thermography might be used for categorizing the vehicle type according to the thermal features of vehicle exteriors and machine learning methods for vehicle type recognition.

The main aim of this paper is to compare the thermal features of electric and conventional (equipped with combustion engines) vehicle exteriors. The thermal cameras can complement or substitute visible spectrum video cameras and other conventional sensors and provide rich classification data linked with vehicle type recognition. The thermal images, obtained through an infrared thermography camera, were evaluated. The important differences between thermal features of these types of vehicle exteriors were found out. The results confirmed the hypothesis that it is possible to use an infrared thermography for vehicle drive categorization, collection of traffic data and eventually for traffic management, Smart city implementation and telematics systems in the towns in future as well.