Nowadays, intelligent vehicles have received a considerable attention among the
researchers to reduce the number of collisions and road accidents. One of the
challenging tasks for these vehicles is road lane detection or road boundaries
detection. In this research, a lane detection algorithm was developed to detect the
right and left lane markers on the road by using two cameras which act as a stereo
vision for the system. It is based on edge detection by using Canny Edge Detection to
reduce unnecessary data on the images and to perform features recognition for the
lane. After the features has been extracted, the algorithm is followed by Hough
Transform method to generate the detected lines on the image obtained from the
stereo vision camera. The algorithm has to work in different environment to be used
in real world applications. The stereo vision algorithm is implemented to generate
disparity map of area. This helps to gain more information on environment, such as the
estimated distance of the lines, the distance of the vehicle to the turns. The experiment
result shows the detection of right and left lane on the road with disparity map to
determine an estimate of the distance of detected lanes from the stereo vision camera.