An Intelligent Lane and Obstacle Detection using YOLO algorithm

Authors

  • Shalu Maharaja Surajmal Institute of Technology, New Delhi
  • Sonia Rathee Maharaja Surajmal Institute of Technology, New Delhi
  • Amita Yadav Maharaja Surajmal Institute of Technology, New Delhi
  • Pooja Kherwa Maharaja Surajmal Institute of Technology, New Delhi
  • Rashmi Gandhi Amity University , Noida

Keywords:

Intelligent Lane detection, canny edge detector, driver support system, obstacle detection, YOLO algorithm

Abstract

It is highly challenging to detect lanes quickly and accurately due to a variety of complex noise, so the main aim goal is to develop a collection of image processing techniques and it produce results quickly and precisely under less-than-ideal circumstances. This paper suggests an intelligent lane recognition technique that utilizes a collection of distinct photos and applies the results to a video stream. The Hough transform is chosen as the most effective beeline detection technique, and the Canny algorithm is chosen as the edge detection technique. The ROI is defined to decrease noise for accurate rise and to increase processing speed to satisfy the real-time need.

For detecting the obstacle, to provide fast implementation and smooth real-time update of the obstacles nearby we are implementing the YOLO algorithm.

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Published

04.11.2023

How to Cite

Shalu, S., Rathee, S. ., Yadav, A. ., Kherwa, P. ., & Gandhi, R. . (2023). An Intelligent Lane and Obstacle Detection using YOLO algorithm . International Journal of Intelligent Systems and Applications in Engineering, 12(3s), 641–648. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3742

Issue

Vol. 12 No. 3s (2024)

Section

Research Article

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