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Self-detection of optical contamination or occlusion in vehicle vision systems

机译:自我检测车辆视觉系统中的光学污染或阻塞

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摘要

We present a novel and practical algorithm for the self-detection problem of contamination or occlusions on the lens of a camera mounted on a vehicle. First, we analyze the intrinsic characteristics of such contamination on the video image. Based on this, cumulative differences are used to segment the static region in the image. A blurred edge detection algorithm based on wavelet decomposition is introduced to confirm if the static region belongs to contamination or an occlusion. Through the combination of these algorithms, contamination or occlusions can be detected. Experimental data are analyzed to show the detection performance of our algorithm and the effect of different contamination or occlusion material.
机译:我们提出了一种新颖实用的算法,可以对车辆上安装的摄像头的镜头上的污染物或阻塞进行自我检测。首先,我们分析视频图像上此类污染的内在特征。基于此,累积差异可用于分割图像中的静态区域。引入了基于小波分解的模糊边缘检测算法,以确认静态区域是属于污染还是被遮挡。通过这些算法的组合,可以检测到污染或阻塞。分析实验数据以显示我们算法的检测性能以及不同污染或阻塞材料的影响。

著录项

  • 来源
    《Optical engineering》 |2008年第6期|067006.1-067006.6|共6页
  • 作者单位

    Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition P.O. Box A0603221 800 Dongchuan Road Shanghai 200240, China;

    Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition P.O. Box A0603221 800 Dongchuan Road Shanghai 200240, China;

    Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition P.O. Box A0603221 800 Dongchuan Road Shanghai 200240, China;

    Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition P.O. Box A0603221 800 Dongchuan Road Shanghai 200240, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    lens contamination detection; lens occlusion detection; cumulative difference; blured edge detection;

    机译:镜片污染检测;晶状体阻塞检测;累积差异;边缘模糊检测;

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