The color identification of automobiles for video surveillance
Yu-Chen Wang, Chen-Ta Hsieh, Chin‐Chuan Han, Kuo‐Chin Fan · 2011
Color identification of automobiles plays a significant in intelligent transportation systems (ITS). In this paper, a novel scheme for color identification of automobile is proposed using the taillight detection and a template matching module. The taillights of cars are detected to find the valid regions of interested (ROIs) for color identification. The color feature vectors generated by 3 by 3 neighboring pixels are classified by a template matching strategy. Seven classes, red, yellow, blue, green, black, white, and gray, are identified in this work. Experimental results have been conducted to show the validity of the proposed method. The averaged accuracy rate 81.71% is achieved and the performance of this scheme is up to 20 frames per second.