[1]金仙力,宋少杰,刘林峰.基于 GMM 的多颜色空间融合的火灾检测算法[J].计算机技术与发展,2022,32(07):75-81.[doi:10. 3969 / j. issn. 1673-629X. 2022. 07. 013]
　JIN Xian-li,SONG Shao-jie,LIU Lin-feng.Fire Detection Algorithm Based on GMM and Multi-color Space Fusion[J].,2022,32(07):75-81.[doi:10. 3969 / j. issn. 1673-629X. 2022. 07. 013]
点击复制

基于 GMM 的多颜色空间融合的火灾检测算法()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年07期
页码:
75-81
栏目:
图形与图像
出版日期:
2022-07-10

文章信息/Info

Title:
Fire Detection Algorithm Based on GMM and Multi-color Space Fusion
文章编号:
1673-629X(2022)07-0075-07
作者:
金仙力; 宋少杰; 刘林峰
南京邮电大学 计算机学院,江苏 南京 210023
Author(s):
JIN Xian-li; SONG Shao-jie; LIU Lin-feng
School of Computer,Nanjing University of Posts and Telecommunications,Nanjing 210023,China
关键词:
颜色模型; 三帧差分法; 自适应高斯混合模型; 形态学方法; 运动检测; 无人机
Keywords:
color model;  three - frame difference method;  adaptive Gaussian mixture model;  morphological method;  motiondetection; UAV
分类号:
TP751
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 07. 013
摘要:
GMM 算法( 高斯混合模型算法) 是一种用于背景建模的高效算法,然而传统的 GMM 算法比较适合于背景很少发生变化的情况,由于无人机这种高速移动平台自身的特殊性,背景时时刻刻在发生变化,因而导致 GMM 算法会出现很多的误判,无法适应这种复杂多变的环境。 为了解决这个问题,提出一种基于 GMM 的多颜色空间融合的火灾检测算法。 首先使用 HSV、XYZ 等多种颜色模型和形态学方法对无人机拍摄的视频帧图像进行预处理,然后在此基础上使用改进的三帧差分法配合改进的自适应 GMM 算法进行烟雾和火焰的检测,最后使用形态学方法进一步去除噪声。 与传统的 GMM 算法相比,该算法能够有效地满足无人机高速移动平台对于算法实时性和检测性能的要求,能够很好地去除噪声,快速、准确地检测出移动的烟雾和火焰。
Abstract:
The GMM algorithm ( Gaussian Mixture Model) is an efficient algorithm for background modeling,but the traditional GMM algorithm is more suitable for the background rarely changes. Due to the particularity of the high-speed mobile platform? ?of the UAV,the background is constantly changing,which leads to a lot of misjudgments in the GMM,unable to adapt to this complex and changeable environment. In order to solve this problem,we propose a fire detection algorithm based? ? on GMM and multi-color space fusion. Firstly,the color models like HSV,XYZ and morphological methods are used to preprocess the video frame images taken by the drone,and then an improved three-frame difference method with an improved adaptive GMM algorithm are applied to detect smoke and flame. Finally,morphological method is to further remove noise. Compared with the traditional GMM algorithm,the proposed algorithm can effectively meet the real-time and detection performance requirements of the UAV high - speed mobile platform,remove noise well,and detect moving smoke and flame quickly and accurately.

相似文献/References:

[1]范保玲 王民 董颖娣.基于肤色检测技术的手势分割[J].计算机技术与发展,2008,(03):105.
　FAN Bao-ling,WANG Min,DONG Ying-di.Hand Gesture Segmentation Based on Skin Color Detection Technology[J].,2008,(07):105.
[2]王建卫.基于对比度增强的彩色图像边缘检测算法[J].计算机技术与发展,2014,24(02):79.
　WANG Jian-wei.An Edge Detection Algorithm of Color Image Based on Contrast Enhancement[J].,2014,24(07):79.
[3]聂建豪,李士进. 基于图像识别的秸秆焚烧事件检测[J].计算机技术与发展,2017,27(05):69.
　NIE Jian-hao,LI Shi-jin. Detection of Straw Burning Event Based on Image Recognition[J].,2017,27(07):69.

更新日期/Last Update: 2022-07-10