Publication Type : Book Chapter
Publisher : Lecture Notes in Computational Vision and Biomechanics
Source : Lecture Notes in Computational Vision and Biomechanics, p.1805-1814 (2019)
ISBN : 9783030006648
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2019
Abstract :
Visual perception of road images captured by cameras mounted within a vehicle is the main element of an autonomous vehicle system. Road detection plays a vital role in a visual routing system for a self-governing vehicle. Effective detection of roads under varying illumination conditions plays a vital role to prevent majority of the road accidents that occur currently. In the current study, a new method using “boundary extraction” technique along with “Hough transform” is proposed for effective road detection. Here, two different algorithms, one using “Canny edge detection” and “Hough transform” and another using “boundary extraction” technique and “Hough transform” were implemented and tested on the same dataset. The comparison of the results of both the techniques showed that the algorithm using “boundary extraction” technique worked better than that which used “Canny edge” detection technique. © Springer Nature Switzerland AG 2019.
Cite this Research Publication : N. Parameswaran, Achan, E., Shree, S., and Manjusha, R., “Road Detection by Boundary Extraction Technique and Hough Transform”, in Lecture Notes in Computational Vision and Biomechanics, 2019, pp. 1805-1814.