Detection and recognition of urban road markings using images

While road lane markings detection was extensively studied, in particular for intelligent vehicle applications, the detection and recognition of all kind of marking such as arrows, crosswalks, zebras, words, pictograms, continuous and discontinuous lane markings was drastically less studied. However, it has many potential applications in the design of advanced driver assistance systems, as well as for asset management along itineraries. An algorithm is proposed which is based on the following processing steps: marking pixel extraction, detection using connected components before Inverse Perspective Mapping and recognition based on the comparison with a single pattern or with repetitive rectangular patterns. The proposed algorithm is able to detect and recognize repetitive markings (such as crosswalks) as well as single patterns (such as arrows). We believe that the proposed algorithm can be extended easily to solve the problem of the identification of all types of markings.