Brunel University Research Archive (BURA) >
Research Areas >
Information Systems and Computing >

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/3230

Title: Traffic sign recognition using discriminative local features
Authors: Ruta, A
Li, Y
Liu, X
Publication Date: 2007
Publisher: Heidelberg: Springer
Citation: In Berthold, M., Shawe-Taylor, J. and Lavrac, N (ed). Advances in Intelligent Data Analysis VII, Aug 2007
Abstract: Real-time road sign recognition has been of great interest for many years. This problem is often addressed in a two-stage procedure involving detection and classification. In this paper a novel approach to sign representation and classification is proposed. In many previous studies focus was put on deriving a set of discriminative features from a large amount of training data using global feature selection techniques e.g. Principal Component Analysis or AdaBoost. In our method we have chosen a simple yet robust image representation built on top of the Colour Distance Transform (CDT). Based on this representation, we introduce a feature selection algorithm which captures a variable-size set of local image regions ensuring maximum dissimilarity between each individual sign and all other signs. Experiments have shown that the discriminative local features extracted from the template sign images enable simple minimum-distance classification with error rate not exceeding 7%.
URI: http://www.springerlink.com/content/vn6qv152k441657t/
http://bura.brunel.ac.uk/handle/2438/3230
ISBN: 978-3-540-74824-3
ISSN: 1611-3349
Appears in Collections:Information Systems and Computing
School of Information Systems, Computing and Mathematics Research Papers

Files in This Item:

File Description SizeFormat
Article_info.txt259 BTextView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.

 


Library (c) Brunel University.    Powered By: DSpace
Send us your
Feedback. Last Updated: September 14, 2010.
Managed by:
Hassan Bhuiyan