大空间火灾的有效检测对预防火灾、保护人员生命财产安全有着至关重要的作用。基于火焰视频图像的检测结果,对分割出的火焰图像进行静态特征描述和分析,提取出火焰候选区域的多种定量特征描绘子,并从颜色特征、纹理特征和形状特征这三个方面来描述火焰影像区域的静态视觉特性。试验结果表明利用火焰影像的颜色矩特征能够区分一般干扰物体;利用纹理特征能有效排除与火焰像素颜色相近的干扰物体;同时,采用圆形度作为火焰图像区域的形状特征描绘子也能排除常见的干扰模式,从而对火灾事件进行准确而有效的识别,减少识别误报率。
It is very important to detect the early fire in large space to protect human life and property security.Here,static visual features description and analysis of the segmented flame image are carried out to extract a variety of quantitative feature descriptors of flame region based on the detection results of flame video image.The static visual features of the flame image area were investigated from the aspects of color feature,texture feature and shape feature,respectively.The experimental results show that the color moment feature of flame image can effectively distinguish the common interferences,and the texture feature can play a very important role in excluding the similar interference color with flame pixels,furthermore,the shape feature is also an effective method to identify the fire flame.So,the static visual features can improve the effectiveness and robustness of flame recognition system,and it can reduce the false alarm rate in the recognition system.