摘要
烟雾检测能够有效预防火灾的发生,以此为出发点,解决了烟雾运动区域出现的"空洞"现象,从而实现了快速、准确地检测视频中烟雾的区域。利用烟雾的非刚体特点,融合颜色、背景模糊以及运动方向的特征对背景更新过程进行建模,然后结合连通域面积消除小干扰区域的影响,提高了基于单一特征的运行期均值法的鲁棒性。实验结果表明,改进的方法能够准确、完整地检测出视频中的烟雾区域,并且处理速度也有所提高。
For detecting smoke which is sign of fire, the "hole" phenomenon which is in the task of smoke detection is resolved in this paper. Considering the non-rigid nature of smoke, the color, blurred background and motion direction are all included to mod- el the process of renewing background. And then the small noise regions are eliminated based on connected area. The improved run-average method is more robust than the one based on single feature. The experimental results show that the proposed method can accurately and efficiently detect the smoke area in video.
出处
《电视技术》
北大核心
2016年第9期95-99,121,共6页
Video Engineering
基金
国家自然科学基金青年项目(61202183
41504115)
陕西省百人计划项目
公安部科技强警基础工作专项项目(2015GABJC50)
陕西省自然科学基础研究计划项目(2015JQ6223)
关键词
烟雾区域检测
运行期均值
多特征融合
smoke region detection
running average
multi-feature fusion