Road markings feature extraction from omni-directional image

Road markings are important information of transport systems for drivers or intelligent vehicle. Efficient road markings feature extraction is pre-requisite to road markings detection, recognition and visual localization. However, most of previous lane markings feature extractors are operating on conventional images, the feature extraction methods for omnidirectional images are rarely considered in road markings detection research. In this paper, three road markings feature extractors for omni-directional images are presented based on different characteristics of road markings. Those lane markings feature extractors are evaluated on real world panoramic image dataset. Experimental results show the feature extractor combing the edge and intensity distribution perform best.