J4 ›› 2012, Vol. 50 ›› Issue (05): 979-986.

• 计算机科学 • 上一篇    下一篇

一种基于块的视频烟雾检测算法

李文辉, 肖林厂, 王莹, 傅博, 刘培勋   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2011-11-10 出版日期:2012-09-26 发布日期:2012-09-29
  • 通讯作者: 王莹 E-mail:wangying_jlu@163.com

A BlockBased Video Smoke Detection Algorithm

LI Wenhui, XIAO Linchang, WANG Ying, FU Bo, LIU Peixun   

  1. College of Computer Science and Technology, Jilin University, Cha
    ngchun 130012, China
  • Received:2011-11-10 Online:2012-09-26 Published:2012-09-29
  • Contact: WANG Ying E-mail:wangying_jlu@163.com

摘要:

为克服传统探测器的缺点, 提高视频烟雾检测算法的检测率, 提出一种基于运动块的视频烟雾检测算法. 该算法先采用帧差法提取运动块, 再分析由运动块组成连通域的面积和运动估计结果, 从而确定疑似烟雾区域. 通过二维离散小波变换提取高、 低频能量特征值, 并根据运动估计结果提取运动保持特征值, 综合各特征值判断是否有烟雾发生. 实验结果表明, 该方法能及时检测到烟雾, 鲁棒性较高、 抗干扰能力强, 能有效预防火灾.

关键词: 烟雾检测; 运动检测; 主运动方向; 运动块; 小波变换

Abstract:

In order to overcome the shortcomings of conventional detectors and improve the detection rate of the current smoke detection algorithms, a new smoke detection approach based on motion block was proposed. Firstly, motion blocks were extracted by frame difference method. Then, candidate smoke regions were determined according to the area and the result of the motion estimation of every connected region. Lastly, the high/low frequency energy eigenvalues were obtained via discrete wavelet transformation and the movement maintenance eigenvalue was obtained according to the result of the estimated direction of movement. These eigenvalues were used to determine whether there is smoke. The experimental results prove that the proposed algorithm is robust, anti\|disturb. It could detect the appearance of smoke timely and prevent fire effectively.

Key words: smoke detection, motion detection, main motion orientation, motion block, wavelet transformation

中图分类号: 

  • TP391