Naveed Ahmed

This is the fourth project that is submitted towards completing Self Driving Car Nanodegree from Udacity. In this project, we develop some advance techniques such as undistortion, perceptive transform, sobel transform to detect the lane lines. To make the visualisation even more intuitive, the radius of curvature of the straight and curvy lanes and the displacement from the center of the lane are also computed. These parameters along with the detected lane lines are shown in the image.

This is the fifth and final project of Term 1 that is submitted towards completing Self Driving Car Nanodegree from Udacity. In this project, we used widely used HOG feature extraction technique to detect vehicles on the road. This is a difficult especially when it comes to detecting vehicles in a video stream because the shape, size and distance of the car from the camera is rapidly changing. The pipeline developed is mostly based on the classroom codes, it is not expected to work very efficient. Yet, it is good enough to train a classifier and detect multiple vehicles.