摘要
针对传统的线圈感应车辆的方法来判断车辆所在的位置,易出现判断失误、更换设备不方便、费用较高的问题,提出一种适应各种光线变化的双目视觉判断车辆位置的方法来解决此问题.该方法根据白天夜晚的光线不同选取白天模式还是夜间模式,白天模式工作主要包括差值图像的中值滤波、二值图像的提取以及背景的分块实时更新,并在此基础上提出了一种背景差分与帧间差分相结合的车辆位置检测方法,该方法能准确的提取阈值以得到精确的目标轮廊,当工作在夜间模式时,开启红外灯切换到红外CCD采集,根据红外灯照射区域的RGB三色值的大小来判断车辆的位置,这种方法解决了车辆灯光对视频采集的影响.通过实验验证了该方法的有效性.此方法能够准确的判断车辆的位置,并很好的控制闸杆的起落.
The traditional method of detecting vehicle location by induction coil vehicle has a lot of problems, such as error in judgment, inconvenient of replacing the equipment and high cost. To solve these problems, this paper proposes a binocular vision method to detect vehicle location. This method adapts to all kinds of light changes. Selecting mode of day or night is determined by the different intensity of light surrounding environment. The mainly works of mode day include the median filtering of difference image, the extraction of binary image and the real-time update of partitioned background. Based on this, the paper proposes a method to detect vehicle location which combine the background subtraction and flame difference methods. This method can accurately extract the threshold value to acquire precise outline of the object. While in night mode, the infrared lamp is opened for switch to infrared CCD acquisition function. It＇s according to the values of RGB which in infrared lamp irradiation area to detect the vehicle location. This method has solved the problem of vehicle lights interference to video acquisition. Finally, the method is experimentally verified, and the results show that it can accurately detect the location of the vehicle and control the brake lever ups and downs.
出处
《计算机系统应用》
2015年第5期57-61,共5页
Computer Systems & Applications
基金
广西桂林电子科技大学创新团队资助
关键词
双目视觉
图像处理
特征提取
模式判断
位置判断
binocular vision
image processing
feature extraction
mode identification
location detection
