This article describes an intelligent system that enables the automatic recognition of road signs from image sequences in road environments. The main difficulties the system has to deal with are related to changes in lighting conditions, obstacles blocking the view, the presence of objects with geometric and chromatic similarities and the absence of previous knowledge about their position and orientation. The application of different techniques allows the system to overcome this variety of problems. Therefore, the road sign recognition system is based on a first pre-processing of images, making use of information about road geometry to isolate those areas of the image where road signs may appear. The detection step uses colour and shape analysis to determine the regions of the image where potential road signs may be located. A third step focuses on recognition and classification using pattern matching and edge feature analysis. The proposed algorithm has been tested in different weather and lighting conditions and roads (one and two-lane roads and motorways), overall, a total of 1200 kilometres with a very high success rate of detection and classification as the experimental results show.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.