Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
Online ISSN : 1881-7203
Print ISSN : 1347-7986
ISSN-L : 1347-7986
Short Notes
A Road Marking Detection System Using Partial Template Matching and Region Estimation by Deep Neural Network
Yuya MIIRyogo MIYAZAKIYuma YOSHIMOTOYutaro ISHIDATakuma ITOKyoichi TOHRIYAMAHakaru TAMUKOH
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2021 Volume 33 Issue 1 Pages 566-571

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Abstract

We improve the performance of a road marking detection system by incorporating You Only Look Once (YOLO) into the processing for vehicle location estimation in autonomous driving technology. The conventional detection method uses a template matching process based on luminance values to detect road marking. However, there are some markings that cannot be detected by this method due to halation by sunlight or strong blurred of road markings. In contrast, the proposed method uses YOLO to search for areas where road marking exists and restricts the area of adaptation for template matching. Owing to this area restriction, the proposed method can prevent the occurrence of false detection, lower the detection threshold for template matching, and reduce the number of previously undetected road markings. In addition, the search area for template matching is restricted, which also can improve the processing speed. Experimental results show that the proposed method is able to reduce the number of undetected road markings compared to the conventional method while keeping the number of false detections to zero. The accuracy of the system was improved by 0.013 and the processing speed was increased by 4.6 FPS compared to the previous method.

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© 2021 Japan Society for Fuzzy Theory and Intelligent Informatics
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