Road Lane Detection with Improved Canny Edges Using Ant Colony Optimization

To reduce accidents and increasing safety, thereby saving lives are one of the context of driver assistance system, among the complex and challenging tasks of future road vehicle is road lane detection. Lane detection is difficult problem because of varying road condition that one can encounter during driving. In this paper a hybrid approach on captured images using ant colony optimization (ACO) on Canny for edge detection then applying few processes in order to detect lanes. Those lanes are extracted using Hough transform. The proposed lane detection system can be applied on painted roads and straight roads. This approach was tested and the experimental results shows that proposed scheme was robust.