摘要
为甄别林火烟雾与大气云雾,提出了基于多种运动特征判据的视频烟雾图像检测算法。首先利用烟雾自身的光学动态特征———光流方向性、相关性、扩散性,分别对连续帧包含烟云的可疑区域进行图像特征标志判别;再经数据融合算法有效区分林火烟雾与大气云雾,克服了依靠单一图像特征检测烟雾的不足。结果表明,光流方向性、相关性、扩散性判别相结合的识别算法能提高森林火灾视频图像的有效识别率。
A smoke detection algorithm combined of multiple motion features was presented. The main purpose of this paper was to separate the smoke-resembling natural phenomena such as clouds, cloud shadows and dust from real smoke. The optical flow property, correlation property based on discrete wavelet transform and diffusion property were matched together to make discrimination. At last, a data weighted fusion algorithm based on statistics theory was applied into smoke detection. Experimental results showed that, compared with the algorithm of detecting smoke using single property, the proposed method can improve the accuracy of smoke detection.
出处
《北京林业大学学报》
CAS
CSCD
北大核心
2013年第3期154-158,共5页
Journal of Beijing Forestry University
基金
国家林业局重点科研项目(2010-01)
关键词
林火烟雾
大气云雾
光流运动
离散小波变换
数据融合算法
forest fire smoke
cloud and mist
optical flow
discrete wavelet transform
data fusionalgorithm based on statistic
