Local Image Features Extraction for Road Signs I'm working on a project to detect a road sign from the Image. Consider the sample image below:



I'm using a heuristic search to detect the road sign within an image. Basically, I want some weak features (colour, shape, zero symmetry within road signs) which can be calculated very fast and their weighted average can be used recognize the road sign.

Currently, I'm searching the entire image to find the road sign which could be of different scale. Since the domain of search is a lot, I tried to reduce it bu by using some heuristics:


Location of sign detect in previous frame (its mostly likely to be near)
Road signs are usually on right sign
Road sign contains enough white pixels


But eventually search needs to stop when it finds the region that contains a road sign. For this purpose, I'm relying on some fast and robust local features that predicts likelihood of containing road sign within given region of an image. Currently, I'm relying mainly on colour and some region props that Matlab provides.

I tried looking for lines and corners within edge map of the region even tried thresholding and looking for rectangle using morphology. But seems like they are too binary either its YES or its NO. In fact in most cases it fails, so my questions what are some nice local features that I could rely on to detect road sign?




I would really appreciate if somebody you guide in the right direction or provide some links or papers that could be helpful for this problem.
Do you know what signs you are looking for? If yes, maybe you could do template matching (e.g. a normalized cross-correlation, available in matlab). It won't work great when signals are getting closer, since the perspective projection will change their appearance, but it should work for mid-range detection.

You can limit your template-matching search to the right side of the road.

There are also template matching algorithms for affine transformations that might be a next step.

Christos