Detection of Vehicle on Infrared Images in Road Traffic
This master thesis is about road user detection with an infrared (IR) camera. Autonomous driving, and driver assistance systems have made very strong progress in recent years. By analysing and processing information form the environment and surroundings, the driver is relieved of responsibility. More and more responsibility for safety is instead placed in the hands of the computer and the sensors. in the daytime it is now very possible using existing trac light sensors to detect signs, cars, cyclists, pedestrians, etc. At night, however, the lighting conditions for burlap cameras are much more unfavourable, and this can lead to inaccurate measurements and thus also to errors in the evaluation of the system under certain circumstances. For example dark-clad pedestrians could be more easily overlooked at night. To reduce the risk of accidents in poor lighting conditions it makes sense to use further sensors, which provide good measurement data even when it is dark and which are not inuenced by poor lighting conditions. One of these sensors is the IR camera. This work deals with the recording of images with an IR camera, and the subsequent analysis of these images with the algorithms of pattern recognition.