Abstract: Building intelligent traffic guide systems has been an
interesting subject recently. A good system should be able to observe
all important visual information to be able to analyze the context of
the scene. To do so, signs in general, and traffic signs in particular,
are usually taken into account as they contain rich information to
these systems. Therefore, many researchers have put an effort on
sign recognition field. Sign localization or sign detection is the most
important step in the sign recognition process. This step filters out
non informative area in the scene, and locates candidates in later
steps. In this paper, we apply a new approach in detecting sign
locations using a new color invariant model. Experiments are carried
out with different datasets introduced in other works where authors
claimed the difficulty in detecting signs under unfavorable imaging
conditions. Our method is simple, fast and most importantly it gives
a high detection rate in locating signs.