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1. LANE DEPARTURE IDENTIFICATION FOR ADVANCED DRIVER ASSISTANCE
ABSTRACT
In this paper, a technique for the identification ofthe unwanted lane departure of a
traveling vehicle on a road isproposed. A piecewise linear stretching function (PLSF) is usedto
improve the contrast level of the region of interest (ROI). Lanemarkings on the road are detected
by dividing the ROI into twosubregions and applying the Hough transform in each subregion
Independently. This segmentation approach improves the computationaltime required for lane
detection. For lane departureidentification, a distance-based departure measure is computedat
each frame, and a necessary warning message is issued to thedriver when such measure exceeds
a threshold. The novelty of theproposed algorithm is the identification of the lane departure only
using three lane-related parameters based on the Euclidean distancetransform to estimate the
departure measure. The use of theEuclidean distance transform in combination with the PLSF
keepsthe false alarm around 3% and the lane detection rate above 97%under various lighting
conditions. Experimental results indicatethat the proposed system can detect lane boundaries in
the presenceof several image artifacts, such as lighting changes, poor lanemarkings, and
occlusions by a vehicle, and it issues an accuratelane departure warning in a short time interval.
The proposedtechnique shows the efficiency with some real video sequences.