Color and shape feature-based detection of speed sign in real-time
Seunggyu Kim, Seongdo Kim, Youngjung Uh, Hyeran Byun · 2012
This paper presents a method for detecting speed sign based on color and shape features in real-time under real-life environment. In our method, Region Of Interest(ROI) is extracted and verified based on shape feature. In the first step, ROI is roughly extracted by segmentation of a red rim and the segments are optimized by the boundary using guided image filtering. Next step, the shape-based detection verifies the extracted red rim. We compare three different shape-based detection methods, RSD, BCT, and STVUE, and the RSD shows the best speed sign detection rate of 93% on the experimental data of 62 images containing 85 speed sign.