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.
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Parameswaran, N.S., Revathi Achan, E., Subhashree, V., Manjusha, R. (2019). Road Detection by Boundary Extraction Technique and Hough Transform. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_165
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DOI: https://doi.org/10.1007/978-3-030-00665-5_165
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