Abstract:
Road sign detection and identification have drawn a lot of attention since the
The 1980s on autonomous vehicle driving systems and the development of intelligent
transportation systems. Video-based methods are commonly used for the
development of such systems. But they are costly and inefficient because of the
limitations in obtaining quality images due to weather conditions, lighting
conditions, and limited range. To overcome those limitations of the existing
method, this research is aiming at developing techniques for detecting road signs
by using Google Street View (GSV) as the source of images. In addition, the
development of vision-based assistance systems requires a large dataset of
images. Currently, it is hard to find a useful Sri Lankan Road Sign Image dataset
that can be used for developing intelligent transport systems. As a byproduct of
the detection process, a valuable dataset of Sri Lankan Road Signs Images could
be formed. It could be useful for future research on developing intelligent
transportation systems, accident-avoidance systems, and driver assistance
systems.
