Circular Traffic Sign Detection in Natural Scenes

Automatic Traffic Sign Detection

This work use basic image processing technique to automatically recognize two different traffic signs (stop sign and yield sign) in an image. The image is first thresholded on RBG domain to separate out the regions with red color, which is those traffic signs usually have, then region mapping is done on the remaining regions, the regions that are either too small and too large are removed since...

Efficient Pedestrian Detection in Urban Traffic Scenes

Pedestrians are important participants in urban traffic environments, and thus act as an interesting category of objects for autonomous cars. Automatic pedestrian detection is an essential task for protecting pedestrians from collision. In this thesis, we investigate and develop novel approaches by interpreting spatial and temporal characteristics of pedestrians, in three different aspects: sha...

Real-time traffic sign detection

An implementation and limited extension of a traffic sign recognition method based on the work by [1] is presented here. This implementation can be extended to target real-time detection. Yield sign, stop sign and red-bordered circular signs are considered. First, image is color segmented based on a thresholding technique. Then, corner features are detected using convolution masks (based on wor...

Recent advances in traffic sign detection

Reliable Fiducial Detection in Natural Scenes

Reliable detection of fiducial targets in real-world images is addressed in this paper. We show that even the best existing schemes are fragile when exposed to other than laboratory imaging conditions, and introduce an approach which delivers significant improvements in reliability at moderate computational cost. The key to these improvements is in the use of machine learning techniques, which ...