  Road region recognition is a main feature that is gaining increasing
attention from intellectuals because it helps autonomous vehicle to achieve a
successful navigation without accident. However, different techniques based on
camera sensor have been used by various researchers and outstanding results
have been achieved. Despite their success, environmental noise like shadow
leads to inaccurate recognition of road region which eventually leads to
accident for autonomous vehicle. In this research, we conducted an
investigation on shadow and its effects, optimized the road region recognition
system of autonomous vehicle by introducing an algorithm capable of detecting
and eliminating the effects of shadow. The experimental performance of our
system was tested and compared using the following schemes: Total Positive Rate
(TPR), False Negative Rate (FNR), Total Negative Rate (TNR), Error Rate (ERR)
and False Positive Rate (FPR). The performance result of the system improved on
road recognition in shadow scenario and this advancement has added tremendously
to successful navigation approaches for autonomous vehicle.
