TY  - BOOK
AU  - Escalera,Sergio
AU  - Baró,Xavier
AU  - Pujol,Oriol
AU  - Vitrià,Jordi
AU  - Radeva,Petia
ED  - SpringerLink (Online service)
TI  - Traffic-Sign Recognition Systems
T2  - SpringerBriefs in Computer Science,
SN  - 9781447122456
AV  - TA1637-1638 
U1  - 006.6 23
PY  - 2011///
CY  - London
PB  - Springer London
KW  - Computer science
KW  - Computer vision
KW  - Computer Science
KW  - Image Processing and Computer Vision
N1  - Introduction -- Background on Traffic Sign Detection and Recognition -- Traffic Sign Detection -- Traffic Sign Categorization -- Traffic Sign Detection and Recognition System -- Conclusions
N2  - This work presents a full generic approach to the detection and recognition of traffic signs. The approach, originally developed for a mobile mapping application, is based on the latest computer vision methods for object detection, and on powerful methods for multiclass classification. The challenge was to robustly detect a set of different sign classes in real time, and to classify each detected sign into a large, extensible set of classes. To address this challenge, several state-of-the-art methods were developed that can be used for different recognition problems. Following an introduction to the problems of traffic sign detection and categorization, the text focuses on the problem of detection, and presents recent developments in this field. The text then surveys a specific methodology for the problem of traffic sign categorization – Error-Correcting Output Codes – and presents several algorithms, performing experimental validation on a mobile mapping application. The work ends with a discussion on future lines of research, and continuing challenges for traffic sign recognition
UR  - http://dx.doi.org/10.1007/978-1-4471-2245-6
ER  -