基于机器视觉的运动目标检测技术研究

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1、硕士学位论文ChapterFiveBasedontraditionalMeanShifttrackingalgorithms,andwellintegratedwiththeaboveelite-family-optimization-basedPCNNmovingobjectdetectionalgorithm,oneexperimentalactivityfortrackingmovingobjectsinrealtimeiscarriedout.Astheexperimentalresultshavesh

2、own,thesaidsoftwareandhardwareplatformsandalgorithmsinthisarticlecaneffectivelyidentifyandtrackmovingobjects.Keywords:Embeddedsystem,Motiondetection,PCNN,MeanshiftIII万方数据基于机器视觉的运动目标检测技术研究插图索引图1.1侦查机器人..........................................................

3、.......................................2图1.2―机遇号‖火星车...........................................................................................2图2.1系统功能图..................................................................................................9图2.2系统

4、供电电路.............................................................................................10图2.3JTAG接口原理图......................................................................................10图2.4OV7725摄像模块............................................

5、.........................................11图2.5OV7725时序图.........................................................................................11图2.6RGB565像素数据输出时序图..................................................................12图2.7uln2003步进电机驱动原理图....

6、...............................................................14图2.8硬件控制平台实物图................................................................................14图2.9机械传动原理图.......................................................................................

7、.15图2.10机械传动平台实物图..............................................................................16图3.1不同模板均值滤波图像对比....................................................................18图3.2不同模板均值滤波图像的直方图.........................................................

8、....19图3.3均值滤波与中值滤波对比图....................................................................20图3.4光流法检测效果图....................................................................................23图3.5