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兵工学报 ›› 2013, Vol. 34 ›› Issue (4): 501-506.doi: 10. 3969/ j. issn. 1000-1093. 2013. 04. 019

• 研究简报 • 上一篇    下一篇

复杂背景下的颜色分离背景差分目标检测方法

吴青青, 许廷发, 闫辉, 徐磊, 吴威, 李相民   

  1. 北京理工大学光电学院光电成像技术与系统教育部重点实验室, 北京100081
  • 上线日期:2013-07-23
  • 通讯作者: 吴青青 E-mail:wuqing3511380@163. com
  • 作者简介:吴青青(1986—),男,硕士研究生。
  • 基金资助:
    国家自然科学基金项目(61027002,61172178),高等学校博士学科点专项科研基金项目(20121101110022)

An Improved Color Separation Method for Object Detection in Complex Background

WU Qing-qing, XU Ting-fa, YAN Hui, XU Lei, WU Wei, LI Xiang-min   

  1. Key Laboratory of Photo Electronic Imaging Technology and System, Ministry of Education of China, School of Optics and Electronics, Beijing Institute of Technology, Beijing 100081, China
  • Online:2013-07-23
  • Contact: WU Qing-qing E-mail:wuqing3511380@163. com

摘要: 针对复杂背景下运动目标检测失检率高的问题,提出了用于复杂背景目标检测改进的 基于RGB 颜色分离的背景差分目标检测方法。主要是对RGB 三通道图像独立进行背景差分运 算,阈值二值化后合并三通道前景图像,得到完整前景目标图像;再利用检测的边缘对前景图像进 行修正,消除光照变化带来的噪声;RGB 三通道使用自适应权值的递推算法进行背景更新。最后 采用实验室采集的图像序列进行了仿真实验,结果表明,该方法在复杂场景下有效识别颜色差异, 避免了灰度值相近而造成的目标缺失,提高了检测精确性。

关键词: 信息处理技术, 颜色分离, 背景差分, 背景更新, 实时处理, 目标检测

Abstract: An improved background subtraction algorithm based on color separation method is introduced to solve the problem of high rate of missing detection of moving object in complex background. First, the current and background color images are individually divided into three images according to RGB chan- nels. Then the background subtraction is made, and the object with threshold in every channel is seg- mented. After that, three result images are combined to obtain a completed foreground image. Edge sub- traction result is used to fix the foreground image so that the noise brought by light is removed. At the same time, the background image from each channel is updated adaptively, in real time and individually. The results show that this method can effectively detect the difference of color which cannot be found by tranditional method because of similar grayscale in complex background.

Key words: information processing, color separation, background subtraction, background update, real time processing, object detection

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