张全法, 费光彦, 王庆峰, 任朝栋. 视频车辆监控系统图像滤波算法的研究[J]. 应用光学, 2012, 33(1): 85-89.
引用本文: 张全法, 费光彦, 王庆峰, 任朝栋. 视频车辆监控系统图像滤波算法的研究[J]. 应用光学, 2012, 33(1): 85-89.
ZHANG Quan-fa, FEI Guang-yan, WANG Qing-feng, REN Chao-dong. Image filtering algorithm for video-based vehicle monitoring systems[J]. Journal of Applied Optics, 2012, 33(1): 85-89.
Citation: ZHANG Quan-fa, FEI Guang-yan, WANG Qing-feng, REN Chao-dong. Image filtering algorithm for video-based vehicle monitoring systems[J]. Journal of Applied Optics, 2012, 33(1): 85-89.

视频车辆监控系统图像滤波算法的研究

Image filtering algorithm for video-based vehicle monitoring systems

  • 摘要: 视频车辆监控系统中图像噪声对背景学习、车辆识别等具有很大影响,已有滤波算法又难以满足系统对滤波效果和速度的综合要求。通过对比不滤波、采用中值滤波或均值滤波时的车辆识别效果和速度,选用均值滤波作为进一步的研究对象。在适当减少计算量的基础上,通过改进数据访问方法和计算方法进一步提高了算法速度,并用Visual C++ 6.0实现了该算法。实验表明,新算法的速度比盒滤波提高了55 %。

     

    Abstract: In video-based vehicle monitoring systems, image noises seriously influenced the results of vehicle recognition, background learning, and so on. The existing filtering algorithms could not meet both the speed and filtering effect requirements of these systems. After comparing the effect and speed of vehicle recognition without filtering and with median filtering or mean filtering, the mean value filtering was selected for further study. By appropriately reducing the amount of calculation, the speed of the new filtering algorithm was increased through improving the processes of data accessing and calculating, and the algorithm was realized with Visual C++ 6.0. Experiment results show that the speed of the new algorithm is 55% faster than box filtering.

     

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