Self‐Driving Cars are no longer the talks of Science fiction. Ever since the DARPA challenge, significant research in the field of autonomous vehicles has been carried out. Various companies are working in this field of research. Various driving support systems are now available these days like lane assist, park assist, etc. These functions are called ADAS or Advanced Driver Assistance Systems. Lane Assistance is basically lane detection i.e. assisting the drivers in recognizing lane lines in front of the car in adverse road conditions. Lane detection is one of the most important tasks required for the successful working of autonomous vehicles or self‐driving cars. Detecting Lane Lines is a challenging task because of the different road conditions while driving. In view of this attribute, this paper proposes the use of Advance Image Processing Techniques and OpenCV functions to detect lanes on a public road along with calculating the radius of curvature of the lane and vehicle position in respect to the road lane i.e. central offset. In this paper, the front facing camera on the hood of the car is used for recording the video of the road in front of the car and feeding that video in the algorithm for better predictions of the road area. Used techniques like Search from Prior and Sliding window to create a more efficient and accurate algorithm better than previous approaches.


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    Title :

    Road Lane Detection Using Advanced Image Processing Techniques


    Contributors:


    Publication date :

    2021-03-29


    Size :

    21 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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