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智能车追寻信标灯过程的图像处理

唐小煜 苏思伟 翁哲 陈群元

唐小煜, 苏思伟, 翁哲, 陈群元. 智能车追寻信标灯过程的图像处理[J]. 华南师范大学学报(自然科学版), 2019, 51(5): 12-17. doi: 10.6054/j.jscnun.2019079
引用本文: 唐小煜, 苏思伟, 翁哲, 陈群元. 智能车追寻信标灯过程的图像处理[J]. 华南师范大学学报(自然科学版), 2019, 51(5): 12-17. doi: 10.6054/j.jscnun.2019079
TANG Xiaoyu, SU Siwei, WENG Zhe, CHEN Qunyuan. Image Processing during the Pursuit of Beacon Lamp by Smart Cars[J]. Journal of South China normal University (Natural Science Edition), 2019, 51(5): 12-17. doi: 10.6054/j.jscnun.2019079
Citation: TANG Xiaoyu, SU Siwei, WENG Zhe, CHEN Qunyuan. Image Processing during the Pursuit of Beacon Lamp by Smart Cars[J]. Journal of South China normal University (Natural Science Edition), 2019, 51(5): 12-17. doi: 10.6054/j.jscnun.2019079

智能车追寻信标灯过程的图像处理

doi: 10.6054/j.jscnun.2019079
基金项目: 

国家自然科学基金项目 61371176

广州市高校创新创业教育项目 2019HD206

详细信息
    通讯作者:

    唐小煜, 讲师, Email:tangxy@scnu.edu.cn

  • 中图分类号: TP242.6;TP391.4

Image Processing during the Pursuit of Beacon Lamp by Smart Cars

  • 摘要: 针对自动化系统中的信标定位技术,提出了一种基于图像进行信标定位的方法,并将其应用于智能车竞赛中.综合考虑真实环境的情况,利用中值滤波算法、动态求阈值算法、交换帧丢弃算法、改进型连通域算法和改进型畸变还原算法等多种算法处理线阵CCD和CMOS摄像头采集的图像,研究该方法的误判率.经实验测试和竞赛中的应用检验,该方法能实现智能车在高速行驶时对信标灯目标的追寻,在强光(约200 lx)、弱光(约75 lx)环境下测试1 000次的误判率分别为1.4%和3.2%.研究结果对解决准确定位信标问题具有重要意义.
  • 图  1  线阵CCD对颜色敏感的示意图

    Figure  1.  The sketch map of CCD sensitivity to color

    图  2  手机和CMOS在相同环境下采集的图像

    Figure  2.  The images taken by mobile phone and CMOS in the same environment

    图  3  交换帧丢弃算法流程图

    Figure  3.  The flow chart of switching frame discarding algorithm

    图  4  四邻域法

    Figure  4.  The four neighborhood method

    图  5  改进型畸变还原算法

    Figure  5.  The improved distortion reduction algorithm

    图  6  信标系统构成图

    Figure  6.  The diagram of beacon system

    图  7  线阵CCD拍摄未亮信标灯的图像信号

    Figure  7.  The image signal of non-luminous beacon lamp captured by linear array CCD

    图  8  CMOS拍摄的信标灯图像

    Figure  8.  The image of beacon lamp taken by CMOS

    图  9  中值滤波算法的前后对比

    Figure  9.  The comparison of median filtering algorithm

    图  10  动态阈值算法的结果

    Figure  10.  The result of dynamic threshold algorithm

    图  11  交换帧丢弃算法测试

    图  12  改进的连通域算法计算结果

    Figure  12.  The results of applying the improved connected domain algorithm

    表  1  误判率测试结果

    Table  1.   The test of misjudgment rate

    分组 照度/lx 测试次数 误判次数 误判率/%
    强光 200 1 000 14 1.4
    弱光 75 1 000 32 3.2
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-02-18
  • 刊出日期:  2019-10-25

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