Information about location and types of road markings are among the crucial information that drivers perceive for a safe and a comfortable driving. Hence road markings are needed to be maintained and updated on a regular basis. With the recent leaps and bounds in the development of self-driving vehicle technology, the importance of regularly maintaining road markings, and moreover automatic detection and recognition of road markings have become more crucial than ever before. Mobile mapping systems (MMS) which is composed of laser sensors, cameras, navigation support systems, etc. are one of the technologies that could be utilized not just for road asset management but also for creating maps related to self-driving vehicles, and so on. In this paper, we have proposed a fully automatic work flow to extract road markings from MMS point clouds. With our proposed algorithm, road markings extraction is largely immune to the change in the absolute value of intensity. The results showed that with our proposed technique, almost all of the road marking could be detected irrespective of the change in absolute intensity as long as the road markings are not faded out entirely. Therefore, our approach of extracting road marking based on relative changes in the intensity of point clouds has a potential to be implemented for a practical purpose.
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