基于证据推理的高铁综合客运 枢纽客流图像背景建模

Background Modeling of Passenger Flow Image in Comprehensive Passenger Transport Hub Based on Dempster-Shafer

  • 摘要: 针对高铁综合客运枢纽客流图像特征,提出基于证据推理的客流图像背景建模方法. 利用均值背景模型和灰度分区处理提高背景模型的处理速度,通过引入证据推理构建合适的mass函数,提高背景灰度值的取值范围的置信度,从而提高背景图像的精确性. 结果表明,该方法原理正确,在高铁综合客运枢纽客流安全预警实际应用中,能够快速准确地生成客流背景图像,保证了客流信息提取的速度和精度.

     

    Abstract: A method was proposed to build background model of passenger flow image in comprehensive passenger transport hub based on dempster-shafer. Mean background model and gray area division were used to improve processing speed of background modeling. Mass function which was from Dempster-Shafer was used to improve confidence of background gray value area and accuracy of background image. Test results show that principle of the method is correct; passenger flow background image can be quickly and accurately built. This method insured the speed and precision of passenger flow information extraction in the passenger flow safety forewarning of high-speed railway comprehensive passenger transport hub.

     

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