Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | ICCAIE 2010 - 2010 International Conference on Computer Applications and Industrial Electronics |
| Pages | 453-457 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 01 Dec 2010 |
| Event | 2010 International Conference on Computer Applications and Industrial Electronics, ICCAIE 2010 - Kuala Lumpur, Malaysia Duration: 05 Dec 2010 → 07 Dec 2010 |
Conference
| Conference | 2010 International Conference on Computer Applications and Industrial Electronics, ICCAIE 2010 |
|---|---|
| Country | Malaysia |
| City | Kuala Lumpur |
| Period | 05/12/10 → 07/12/10 |
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Colour-based bottom-up saliency for traffic sign detection. / Le Ngo, Anh Cat; Ang, Li Minn; Seng, Kah Phoai; Qiu, Guoping.
ICCAIE 2010 - 2010 International Conference on Computer Applications and Industrial Electronics. 2010. p. 453-457 5735122.Research output: Book chapter/Published conference paper › Conference paper
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 - 2010/12/1
Y1 - 2010/12/1
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
UR - http://www.scopus.com/inward/citedby.url?scp=79953878376&partnerID=8YFLogxK
U2 - 10.1109/ICCAIE.2010.5735122
DO - 10.1109/ICCAIE.2010.5735122
M3 - Conference paper
AN - SCOPUS:79953878376
SN - 9781424490554
SP - 453
EP - 457
BT - ICCAIE 2010 - 2010 International Conference on Computer Applications and Industrial Electronics
ER -