• C P Adarsh
• C P Adesh
• Anshul K Shaji
• Sebin k George

An Autonomous vehicle is a driverless car which can guide itself without the help of human contact. This advanced technology is finding its relevant place in today’s international market. Lane detection, lane marker tracking, advanced image processing, GPS tracking are few research areas in this domain. This paper concentrates on Lane detection and lane marking. Multiple images are captured and processed periodically using an advanced camera placed on top of the vehicle. Each of these photos is processed and data is simulated. First, ROI (Region of Interest) is calculated in order to increase the processing speed and to reduce complexity in its procedure. Proper filtering techniques are carried out to reduce the noise that can superimpose with image quality. This is followed by binary conversion and relevant edge detection technique. Hough Transform is used to extract lines from the image. Increase in the threshold value of Hough transforms increases the possibility to map lanes accurately. A proper coloring method is used to improve the visibility of lane and thus helps the autonomous vehicle to follow its path through mapped lanes. The analysis shows that this algorithm produces effective results as compared to that of the existing algorithms.

Lane detection, Region of interest, edge detection, multiple filters, Hough transform

"Efficient image processing technique for lane detection in autonomous vehicle", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.436-442, January-2019, Available :http://www.jetir.org/papers/JETIR1901B58.pdf

"Efficient image processing technique for lane detection in autonomous vehicle", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp436-442, January-2019, Available at : http://www.jetir.org/papers/JETIR1901B58.pdf