Research Information System
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, İzmir, Turkey, 2 - 05 May 2018, pp.1-4
This paper proposes a robust and effective visionbased
lane detection approach. First, two binary images are
obtained from the region of interest of gray-scale images. The
obtained binary images are merged by a novel neighborhood
AND operator and then transformed to a bird’s eye view (BEV)
via inverse perspective mapping. Then, gaussian probability
density functions are fit to the left and right regions of a
histogram image acquired from the BEV. Finally, a polynomial
lane model is estimated from the identified regions. Experimental
results show that the proposed method accurately detects lanes in
complex situations including worn-out and curved lanes.