A geometric framework for stop sign detection
Qi Li, Gongbo Liang, Yongyi Gong · 2015
In this paper, we propose a geometric framework for stop sign detection based on polylines. We first propose a scheme for the extraction of 1-piece and 2-piece polylines from connected components of edge pixels. This scheme contains three basic steps: i) dominant point extraction, ii) linearity verification, and iii) partitioning. We then propose a polyline-based framework for stop sign detection. Specifically, the framework consists of three parts: i) extraction of 1-/2-piece polylines, ii) generation of regular octagon candidates, and iii) scoring regular octagon candidates. We test the proposed framework in a dataset that contains 500 stop sign images, and obtain a result of 96% detection rate.