Title :
Colour-based bottom-up saliency for traffic sign detection
Author :
Le Ngo, Anh Cat ; Ang, Li-Minn ; Seng, Kah Phooi ; Qiu, Guoping
Author_Institution :
Electron. Dept., Univ. of Nottingham, Semenyih, Malaysia
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.
Keywords :
computer vision; image colour analysis; object detection; traffic engineering computing; UNMC automotive vision database; colour-based bottom-up saliency method; computer vision system; image processing techniques; red-green-blue values; traffic sign detection; Feature extraction; Gaussian distribution; Humans; Image color analysis; Pixel; Roads; Visualization;
Conference_Titel :
Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-9054-7
DOI :
10.1109/ICCAIE.2010.5735117