  In the past few years, researches on advanced driver assistance systems
(ADASs) have been carried out and deployed in intelligent vehicles. Systems
that have been developed can perform different tasks, such as lane keeping
assistance (LKA), lane departure warning (LDW), lane change warning (LCW) and
adaptive cruise control (ACC). Real time lane detection and tracking (LDT) is
one of the most consequential parts to performing the above tasks. Images which
are extracted from the video, contain noise and other unwanted factors such as
variation in lightening, shadow from nearby objects and etc. that requires
robust preprocessing methods for lane marking detection and tracking.
Preprocessing is critical for the subsequent steps and real time performance
because its main function is to remove the irrelevant image parts and enhance
the feature of interest. In this paper, we survey preprocessing methods for
detecting lane marking as well as tracking lane boundaries in real time
focusing on vision-based system.
