关键词: 智能交通系统, 车标识别, 图像质量, 主成分分析

Abstract: Concerning the low recognition rate of vehicle-logo images which were shot outdoor under moving conditions and with a variety of qualities, a new recognition method was proposed based on image quality and Principal Component Analysis (PCA) subspace. Firstly, the image fuzzy degree was computed according to fuzzy theory. Then the training samples were divided into different subsets in terms of fuzzy degree and their corresponding PCA subspaces were constructed. At last, the vehicle-logo was recognized in the specific subspaces which were chosen by the vehicle-logos fuzzy degree. The experimental data show that the reconstruction errors based on this method are less than those of traditional PCA subspace, thus the proposed method has more powerful capability in pattern depiction and can obtain higher recognition rate. The comparative test results further indicate the validity of this method.

Key words: Intelligent Transportation System(ITS), vehicle-logo recognition, image quality, Principal Component Analysis (PCA)