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4 March 2015 Detection and recognition of road markings in panoramic images
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Proceedings Volume 9407, Video Surveillance and Transportation Imaging Applications 2015; 940708 (2015)
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Detection of road lane markings is attractive for practical applications such as advanced driver assistance systems and road maintenance. This paper proposes a system to detect and recognize road lane markings in panoramic images. The system can be divided into four stages. First, an inverse perspective mapping is applied to the original panoramic image to generate a top-view road view, in which the potential road markings are segmented based on their intensity difference compared to the surrounding pixels. Second, a feature vector of each potential road marking segment is extracted by calculating the Euclidean distance between the center and the boundary at regular angular steps. Third, the shape of each segment is classified using a Support Vector Machine (SVM). Finally, by modeling the lane markings, previous falsely detected segments can be rejected based on their orientation and position relative to the lane markings. Our experiments show that the system is promising and is capable of recognizing 93%, 95% and 91% of striped line segments, blocks and arrows respectively, as well as 94% of the lane markings.
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Cheng Li, Ivo M. Creusen, Lykele Hazelhoff, and Peter H. N. de With "Detection and recognition of road markings in panoramic images", Proc. SPIE 9407, Video Surveillance and Transportation Imaging Applications 2015, 940708 (4 March 2015);


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