快速消除车辆阴影的多阈值图像分割法

任朝栋, 张全法, 李焕, 荆宜青

任朝栋, 张全法, 李焕, 荆宜青. 快速消除车辆阴影的多阈值图像分割法[J]. 应用光学, 2010, 31(6): 961-964.
引用本文: 任朝栋, 张全法, 李焕, 荆宜青. 快速消除车辆阴影的多阈值图像分割法[J]. 应用光学, 2010, 31(6): 961-964.
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REN Chao-dong, ZHANG Quan-fa, LI Huan, JING Yi-qing. Quick elimination of vehicle shadow by multi threshold image segmentation[J]. Journal of Applied Optics, 2010, 31(6): 961-964.
Citation: REN Chao-dong, ZHANG Quan-fa, LI Huan, JING Yi-qing. Quick elimination of vehicle shadow by multi threshold image segmentation[J]. Journal of Applied Optics, 2010, 31(6): 961-964.
shu

快速消除车辆阴影的多阈值图像分割法

  • 郑州大学物理工程学院,河南郑州450001

详细信息
    通讯作者:

    任朝栋(1983-)，男，河南平顶山人，郑州大学物理工程学院硕士研究生，主要从事计算机图像处理方面的研究工作。

  • 中图分类号: TP391.41

Quick elimination of vehicle shadow by multi threshold image segmentation

  • School of Physics and Engineering,Zhengzhou University,Zhengzhou 450001,China

摘要

    摘要
  • 摘要: 视频图像分割时的运动阴影由于与被测对象的相似性而常被误判为被测对象，传统的阴影检测方法一般难以满足实时智能交通系统对处理速度的要求。为此，提出用多阈值法分割图像，将灰度化的当前图像与背景差分，再用正、负两个阈值对其二值化，在分割出深色和浅色被测对象的同时消除阴影。实验表明，将这种方法应用于运动车辆的检测，具有速度快和阴影消除效果好等特点，可应用于实时的运动目标检测和跟踪等领域。
    Abstract: Moving shadow is usually misinterpreted as part of moving object because of its similarity with the object in video target segmentation, and the processing speed of traditional shadow elimination method can not meet the requirement of real-time intelligent transportation system. A new shadow elimination method is proposed. In this method, every color image of a video is transformed into gray images; and difference image is obtained by calculating the difference between the gray image and its background; then the difference images are transformed into binary images with a positive threshold and a negative threshold. By selecting these two thresholds appropriately for both light-colored and deep-colored objects, only target object remains in the binary images. In the experiments of real-time vehicle detection, this method demonstrates a good performance of quick shadow elimination compared to traditional method. It can be applied to moving object detection, tracking and other real-time applications.
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    • 参考文献(1)
  • ［1］韩梅,纪明,史志富,等.一种实时检测遮挡阴影的算法［J］.应用光学, 2009,30(5):797-801.
    HAN Mei, JI Ming, SHI Zhi-fu, et al. Shadow detection algorithm based movement feature［J］. Journal of Applied Optics, 2009,30(5):797-801.(in Chinese with an English abstract)
    ［2］张玲,程义民,葛仕明,等.基于纹理的运动阴影检测方法［J］.光电工程, 2008，35(1)：80-84.
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    ［3］姚志均,许毅平,魏蛟龙,等.视频监控系统中运动目标的检测和阴影抑制［J］.计算机工程与应用, 2007，43(21)：232-234.
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    ［8］陈功,周荷琴,严捷丰.采用UKF建模的实时背景提取和运动阴影检测［J］.中国图像图形学报, 2009，14(5)：931-937.
    CHEN Gong, ZHOU He-qin, YAN Jie-feng. Real-time background subtraction and moving shadow detection based on UKF modeling［J］. Journal of Image and Graphics, 2009，14(5)：931-937. (in Chinese with an English abstract)
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出版历程
  • 刊出日期:  2010-11-30

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