中文摘要：

传统方法将车标定位与识别分开进行,定位的误差将会给后续的识别带来影响,并且车标图像具有低分辨率、低质量的特点。提出了一种新颖的车标定位和识别有机整合的方法。通过稀疏取样对样本图像进行取点采样,将点集分为邻近点集和非邻近点集,分别对其提取梯度特征和明暗特征,构建特征库,对车标粗定位区域进行多尺度扫描。实验结果表明,该方法在车标检测识别效率方面具有更大的优势,而且对于不同类型的车标图像都具有鲁棒性。

英文摘要：

The vehicle logo location and recognition are separated in the traditional method, the location errors will affect the subsequent recognition, at the same time the vehicle logo images are with low resolution and poor quality. Thus, a novel method was proposed which integrated the vehicle logo location and recognition organically. The sample images were sampled by sparse sampling, and then the point set was divided into adjacent point set and non adjacent point set, and the gradient feature and light and dark feature were extracted respectively, constructing the feature library. The logo coarse location area was multi-scale scanned. The experimental results show that the proposed method is superior to other advanced algorithms on the vehicle detection and recognition efficiency, and robust to the different types of logo images.