Abstract
Knowing the location of the road in an intelligent traffic systems is one of the most used solutions to ease vehicle detection. For this purpose we propose a vehicle recognition algorithm which performs a real time automatic detection of the zones which vehicles occupy. Such algorithm is capable of functioning under extreme conditions such as low resolution, low capture angle and gray scale images.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kanhere, N.K., Birchfield, S.T.: IEEE. Real-Time Incremental Segmentation and Tracking of Vehicles at Low Camera Angles Using Stable Features.
Corke, P.I.: Machine Vision Toolbox, corkecsiro.au
Ha*, D.M., Lee, J.-M., Kim, Y.-D.: Neural-edge-based vehicle detection and traffic parameter extraction
Wei Zhang, Q.M., Wu, J., Yang, X., Fang, X.: Multilevel Framework to Detect and Handle Vehicle Occlusion.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Peñate Sánchez, A., Quesada-Arencibia, A., Travieso González, C.M. (2012). Real Time Vehicle Recognition: A Novel Method for Road Detection. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2011. EUROCAST 2011. Lecture Notes in Computer Science, vol 6928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27579-1_46
Download citation
DOI: https://doi.org/10.1007/978-3-642-27579-1_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27578-4
Online ISBN: 978-3-642-27579-1
eBook Packages: Computer ScienceComputer Science (R0)