White Lane Detection Using Semantic Segmentation

This paper deals with the application of machine learning techniques to the detection of white lanes for autonomous driving assistance using only a single visual camera. When performing white line detection, a method called semantic segmentation using fully convolutional network is used. This method is chosen to flexibly detect the shape of objects, since detection of white lanes cannot be done well with rectangular detection. The convolutional neural network which is characterized by the absence of fully connected layer outputs an image for a given input. FCN-8s are used for fully convolutional network. FCN-8s has an easy-to-understand structure and an advantage of being easy to create. In addition, we also created a dataset manually by extracting white lines from public roads and used it for training and testing the learning algorithm. Our segmentation algorithm is found to accurately detect the white lane markings from the dataset.