Lane departure warning system based on Hough transform and Euclidean distance

Unintended lane departure due to driver's inattention, drowsiness, or fatigue is the leading cause that is risking lives of people. Lane departure warning (LDW) system plays an important role in improving driver's safety. It warns the driver if the vehicle begins to drift out of its lane. This paper presents LDW system based on the Hough transform and Euclidean distance. Initially, histogram equalization is used to enhance the contrast level of input image. In order to improve the speed and accuracy of the system, we divide the selected ROI into two subregions. Then Hough transform is used for lane detection in which left and right lane marking are detected independent of each other. Finally, lane departure identification is carried out using lane related parameters, estimated on the basis of Euclidean distance. The proposed methodology is tested on several video sequences. Experimental results indicate that proposed system provide high lane detection and low false warning rate.