It is important for self-driving cars to have the ability to see the world like we see it. The fundamental object what the self-driving cars should see is the lane lines. Therefore, I have used the computer vision algorithms to detect lines. According to my algorithm, I have used the Canny edge detection technique which eventually can detect any color of lane lines. It transforms the RGB image into grayscale and then convert the grayscale into a gradient image. Later, these edges become a key to apply the Hough transform technique, thus detect the lane lines. This technique joins the edges which was voted as the line of best fit in describing my data. To check the performance of the algorithm, I made the comparison of pixels and found the distance between them, hence found the accuracy of it.