事故车辆图像特征点的自动匹配

Automatic Matching of Image Feature Points of Accident Vehicle

针对一般自动匹配成果难以直接应用到交通事故勘查的立体匹配中这一问题,文中提出了一种事故车辆图像特征点的自动匹配方法,应用SIFT理论和BP神经网络理论构造了事故车辆图像特征点的自动匹配模型,并进行了实验验证.研究结果表明,该匹配方法可以实现立体像对中任一选定目标的自动匹配,匹配的结果能够作为精匹配的提示.该匹配方法可大幅度提高立体匹配选点的效率,提高交通事故立体视觉系统的量测速度,并且可以作为一种技术手段为确认车牌被遮挡的违章车辆提供借鉴.

As the common automatic matching is difficult to meet the requirements of stereo matching for traffic accident investigation, a new automatic matching method of image feature points of accident vehicle is proposed, and the corresponding model is established based on the SIFY theory and the BP neural network. Some experiments are then performed to verify the proposed model. The results show that the proposed method is suitable for the automatic matching of any selected object in a stereopair, and the matching results can be used as a reference to the precise matching. It is also indicated that the proposed method greatly improves the efficiency of stereo keypoint selection and accelerates the measurement in stereovision system. Moreover, as an efficient technology, it provides a reference for the identification of vehicles with covered license.