Hybrid approach to road detection in front of the vehicle

Recently, autonomous cars have become the main aim of the automotive industry. There are many image processing problems. One of them is road detection which is the main topic of this article. The purpose of this paper is to compare two different approaches which are Multilayer Perceptron and method based on illuminant invariance to solve the problem of road detection using images from camera located in front of the vehicle. Further, new approach is proposed which uses two mentioned methods combined together to reach better results in terms of accuracy and to achieve better robustness of single method. The comparison of the algorithms was based on images from KITTI dataset. Algorithms were examined in terms of time execution and classification metrics.