Review. Machine learning techniques for traffic sign detection
It provides a synthesis for researchers working on driver assistance systems, but is incremental as it only reviews existing methods.
This paper reviews existing machine learning techniques for traffic sign detection, categorizing them into general machine learning and neural networks, and compares their features without presenting new results.
An automatic road sign detection system localizes road signs from within images captured by an on-board camera of a vehicle, and support the driver to properly ride the vehicle. Most existing algorithms include a preprocessing step, feature extraction and detection step. This paper arranges the methods applied to road sign detection into two groups: general machine learning, neural networks. In this review, the issues related to automatic road sign detection are addressed, the popular existing methods developed to tackle the road sign detection problem are reviewed, and a comparison of the features of these methods is composed.