Road detection based on illuminant invariance and quadratic estimation

Road extraction is an important part of the intelligent vehicle systems for automatic driving, navigation, and traffic warning. For the complicated road scene, we present a road detection method based on illumination invariant image and quadratic estimation. The algorithm firstly extracts the illumination invariant image, and a priori triangular road region is used as the color sample to analyze the illumination invariant image and obtain the probability maps. Next, based on the histogram analysis, the combined probability map is significantly resettled, and the road region is estimated for the first time. Then gradient images of the illumination invariant image and the probability map are extracted, and the gradient image is analyzed by the estimated road region. Finally, the effective road boundary is extracted, and the more accurate road region is obtained. The experimental results show that our method can adapt to the road image in a variety of environments. Compared with other algorithms, our algorithm is more stable, and the computational efficiency is improved obviously.