TY - GEN
T1 - Colour-based bottom-up saliency for traffic sign detection
AU - Le Ngo, Anh Cat
AU - Ang, Li Minn
AU - Seng, Kah Phoai
AU - Qiu, Guoping
PY - 2010
Y1 - 2010
N2 - On roads, drivers can detect traffic sign extraordinarily fast and accurately; however, the computer vision system does not easily imitate this natural ability although using a lot of image processing techniques. This weakness can be tackled by a bottom-up visual saliency method based on traffic-sign colours which occupy certain ranges of RGB values. These values can be used to modulate the bottom-up visual saliency, so the proposed system can focus on traffic signs detection. The method is tested on the UNMC Automotive Vision Database and compared with results of the purely bottom-up visual saliency method.
AB - On roads, drivers can detect traffic sign extraordinarily fast and accurately; however, the computer vision system does not easily imitate this natural ability although using a lot of image processing techniques. This weakness can be tackled by a bottom-up visual saliency method based on traffic-sign colours which occupy certain ranges of RGB values. These values can be used to modulate the bottom-up visual saliency, so the proposed system can focus on traffic signs detection. The method is tested on the UNMC Automotive Vision Database and compared with results of the purely bottom-up visual saliency method.
UR - http://www.scopus.com/inward/record.url?scp=79953878376&partnerID=8YFLogxK
U2 - 10.1109/ICCAIE.2010.5735122
DO - 10.1109/ICCAIE.2010.5735122
M3 - Conference Proceeding
AN - SCOPUS:79953878376
SN - 9781424490554
T3 - ICCAIE 2010 - 2010 International Conference on Computer Applications and Industrial Electronics
SP - 453
EP - 457
BT - ICCAIE 2010 - 2010 International Conference on Computer Applications and Industrial Electronics
T2 - 2010 International Conference on Computer Applications and Industrial Electronics, ICCAIE 2010
Y2 - 5 December 2010 through 7 December 2010
ER -