DocumentCode
2799448
Title
Integrated speed limit detection and recognition from real-time video
Author
Eichner, Marcin L. ; Breckon, Toby P.
Author_Institution
Cranfield Univ., Cranfield
fYear
2008
fDate
4-6 June 2008
Firstpage
626
Lastpage
631
Abstract
Here we propose a complete system for robust detection and recognition of the current speed sign restrictions from a moving road vehicle. This approach includes the detection and recognition of both numerical limit and national limit (cancellation) signs with the addition of automatic vehicle turn detection. The system utilizes both RANSAC-based colour-shape detection of speed limit signs and neural network based recognition whilst turn analysis relies on an optic flow based method. As primary detection is based on a robust colour and shape detection methodology this results in a real-time algorithm that is invariant to variable road conditions. The integration of both limit, cancellation and vehicle turn detection within the bounds of real-time system performance represents an advance on prior work within this field.
Keywords
image colour analysis; image motion analysis; image recognition; neural nets; object detection; random processes; real-time systems; road vehicles; sampling methods; traffic engineering computing; video signal processing; RANSAC-based colour-shape detection; image colour; moving road vehicle; national limit sign; neural network; numerical limit sign; optic flow; real-time system; real-time video; speed limit detection; speed limit recognition; speed limit sign; speed sign restriction; turn analysis; vehicle turn detection; Image motion analysis; Neural networks; Optical computing; Optical fiber networks; Real time systems; Road vehicles; Robustness; Shape; System performance; Vehicle detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Vehicles Symposium, 2008 IEEE
Conference_Location
Eindhoven
ISSN
1931-0587
Print_ISBN
978-1-4244-2568-6
Electronic_ISBN
1931-0587
Type
conf
DOI
10.1109/IVS.2008.4621285
Filename
4621285
Link To Document