计算机与现代化

• 图像处理 •    下一篇

基于串并行处理的多特征交通视频烟雾检测算法

  

  1. 华南理工大学土木与交通学院,广东广州510641
  • 收稿日期:2016-11-14 出版日期:2017-04-20 发布日期:2017-05-08
  • 作者简介:陈康(1992-),男,江西鄱阳人,华南理工大学土木与交通学院硕士研究生,研究方向:车路协同与安全控制,道路交通安全; 李耀华(1988-),男,河北武安人,硕士研究生,研究方向:图像处理,人脸检测; 通信作者:游峰(1977-),男,贵州遵义人,副教授,博士,研究方向:车路协同与安全控制,道路交通安全; 陈润丰(1994-),男,广东惠州人,硕士研究生,研究方向:交通规划。
  • 基金资助:
    国家自然科学基金资助项目(51408237,51108192); 广东省公益研究与能力建设专项项目(x2tjB2161520); 华南理工大学2016年度学生研究计划SRP

Smoke Detection Algorithm About Video Image with Multiple Features Based on Serial and Parallel Processing Model

  1. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, China
  • Received:2016-11-14 Online:2017-04-20 Published:2017-05-08

摘要: 提出一种串并行处理结合的烟雾检测算法,对视频序列进行混合高斯背景建模提取运动前景,圈取感兴趣区域,进而对其进行多特征并行分析。颜色特征分析时,在RGB空间下对各通道信息进行归一化处理,结合烟雾的颜色特征进行阈值判断。形状特征分析时用不规则度突变量作为度量标准,用统计分析的方法,对视频图像中的不规则度突变做监测,检测图像的不规则度的突变情况。采用小波变换法检测图像中的高频信息,结合烟雾扩散快的特点,将小波系数变化率作为检查标准。综合多特征进行加权分析,建立综合判据公式对视频图像作烟雾检测报警。

关键词: 烟雾检测, 串并行处理, 混合高斯模型, 颜色分析, 形状分析, 小波分析, 动态阈值

Abstract: This paper presents a smoke detection algorithm characterized by combination of serial and parallel processing model. This algorithm analyzes multiple features of video sequence by extracting the motion foreground of Gaussian mixture background modeling, and circling interested regions. When analyzing color feature, the information of each channel is normalized in RGB space, and the threshold value is judged according to the color characteristics of the smoke. When analyzing the shape feature, the statistical method is adopted to monitor the irregular degree of the video image with the measurement standard of irregular degree of break variable. Taken change rate of wavelet coefficient as check standard, the wavelet transform method is adopted to detect the high frequency information in the image with the combination of the characteristics of smoke diffusion. Based on the weighted analysis of multiple features, a comprehensive criterion is established for the detection and alarm of smoke detection in video image.

Key words:  smoke detection, serial and parallel processing model, Gaussian mixture model, color analysis, shape analysis, wavelet analysis, dynamic threshold

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