Exploring the traffic sign recognition problem

Abstract

In this project a technique suggested as a solution for traffic sign recognition is presented. Scale-Invariant Feature Transform (SIFT) was examined to perform recognition (Detection and Classification). SIFT proved to be excellent in the detection and classification of traffic signs. Since SIFT is orientation invariant, orientation histogram used to make the feature orientation dependent. We used two databases of traffic signs images for testing the system, the result showed a success rate of (96.67%).