Image segmentation and pattern recognition for road marking analysis

This paper describes a method of road segmentation and pattern recognition for road marking analysis. Efficient segmentation and pattern recognition are difficult due to other vehicles, outdoor lighting or shadows. Rectilinear marking and arrow extraction is carried out by mathematical morphology in order Io take into account geometrical characteristics (size for example). Thus, rectilinear objects such as white lines are extracted by Hough transform. We use Fourier descriptors to describe the boundaries of an object. Thus, a KNN classifier recognizes the object from a training base built with simulated data. Finally, the road is reconstructed with the elements detected in each image. Some results of the road segmentation and pattern recognition in difficult situations are shown. We introduce an interpolation method to deal with the absence of marking due to. for instance, dirty marking, occlusion by other vehicles or poor visibility.