leo2105/carnd-lanelines-p1

Project 1 of Udacity Self-Driving NanoDegree

Finding Lane Lines on the Road

Writeup

---

Finding Lane Lines on the Road

The goals / steps of this project are the following:

• Make a pipeline that finds lane lines on the road
• Reflect on your work in a written report

---

Reflection

1. Describe your pipeline. As part of the description, explain how you modified the draw_lines() function.

My pipeline consisted in 6 steps. First, I converted the images to grayscale, then I used the function GaussianBlur with kernel size equal to 5 to reduce image noise and reduce details. Later, I used canny transformation to find lines. Moreover, I used Hough transformation that returns an image with hough lines drawn. After, I used the draw_lines function to extrapolate two main lines that I chose with respect to its slope. Finally, I used weighted_img function to combine the two last lines with the original image.

In order to draw a single line on the left and right lanes, I modified the draw_lines function by using equation line to extrapolate. I chose these lines with respect to their slope. For example, the left line should be with the greatest slope and the rigth line should be with the lowest slope. Finally, I used weighted_img function to combine the two last lines with the original image.

I would like to show an image when I ran all of pipeline.

2. Identify potential shortcomings with your current pipeline

One potential shortcoming would be what would happen when left line and right line have the same slope. Because, I just choose one line by positive slope and one line by negative slope.

Another shortcoming could be if left line and right could not be recognized when I perform Hough Transformation.

3. Suggest possible improvements to your pipeline

A possible improvement would be to choose another a better way to find the left and right line perfectly.