Extraction of road traffic sign information based on a vehicle‐borne mobile photogrammetric system

Abstract

AbstractA new approach to automatically extracting road traffic sign information based on a vehicle‐borne mobile photogrammetric system (VMPS) is proposed in this paper. The method can be divided into four steps: (a) traffic sign detection in a single image; (b) geometric information computation in a stereopair; (c) semantic information recognition; and (d) stereoscopic information consistency verification. In order to enhance the robustness and adaptability of the approach, colour recognition probabilistic neural networks (PNNs) based on pixel vectors, together with shape‐identification PNNs based on central projected vectors, are used during the traffic sign detection and recognition steps. The proposed approach is applied to many real‐scene stereopairs taken by VMPS at different times and places. Experimental results demonstrate its feasibility and effectiveness.