实时自动道路标志识别用特征驱动的方法外文文献翻译、中英文翻译、外文翻译.doc

Automatic real-time road marking recognition using a feature driven approach Alireza Kheyrollahi · Toby P. Breckon Abstract Automatic road marking recognition is a key problem within the domain of automotive vision that lends support to both autonomous urban driving and augmented driver assistance such as situationally aware navigation systems. Here we propose an approach to this problem based on the extraction of robust road marking features via a novel pipeline of inverse perspective mapping and multi-level binarisation. A trained classifier combined with additional rule-based post-processing then facilitates the real-time delivery of road marking information as required. The approach is shown to operate successfully over a range of lighting, weather and road surface conditions. Keywords Computer vision · Mobile robotics · Road marking recognition · Vanishing point detection · Intelligent vehicles 1 Introduction Autonomous driving and road intelligence have been the focus of attention for many computer vision researchers over the last 20 years [1]. Although significant achievement has been made in developing a vehicle that can perform some form of autonomous guided driving, progress has been slow because of the problems of speed, safety and the real-time complexity of the on-road situation. A human driver gathers constant and numerous visual information from the road and the surroundings. Our brain is quite efficient in analysing this information and responding quickly by an appropriate course of action. For a computer vision system to be able to display a similar ability, it must encompass various detection abilities, each of which has been subject of significant research activity [2–4]. Whilst work on lane detection and tracking is significant [5,22], the literature on road marking recognition is limited with no reported work for real-time on-road text recognition. While road marking (including arrows) and text recognition is a relatively simple task for huma