小波变换在交通参数检测中的应用

针对视频交通图像的特点,提出了一种将灰度判断与边缘检测相结合来检测交通参数的方法;综合了灰度检测和边缘检测的优点,采用帧平均法来处理视频流,可以减小由于摄像头抖动或背景微小变化而产生的误差;分析了小波变换的特点,应用小波变换对交通图像进行车辆边缘检测,对不同尺度小波变换后的水平方向、垂直方向和对角线方向的高频信息,用互能量交叉的方法进行噪声抑制,突出主要边缘,最后,在车辆边缘识别基础上获得车流量、车速等相关交通参数;实验结果表明,此方法简单、有效,获得了较满意的检测结果。

Application of Wavelet Transformation in Traffic Parameter Detection

Considering the characteristics of traffic image, a scheme of traffic parameter detection is proposed based on the combination of gray value and edge detection. A frame averaging method is introduced to reduce the error brought by camera wobbling or background chan- ging. It analyzes the feature of wavelet transform, and detects the edge of vehicle with wavelet transform. With high frequency information of horizontal, vertical and diagonal directions of wavelet transform trader different scales, using the method of nlutual energy cross to restrain noise. This method can give prominence to main edge. Finally, traffic parameters such as vehicle flow and speed is obtained. These opera tions are aDDlied with reason.and the computation time is reduced. Experimental results show that it is a simple and feasible method.