强光干扰下的火焰前景提取技术研究

火焰前景提取是视频型火灾检测算法的重要步骤,也是后续火焰特征识别算法的基础。针对现有火焰前景提取算法在强光干扰下或在背景与火焰颜色相近时无法正确提取火焰前景的问题,提出一种新的火焰前景提取算法。首先通过计算瞬时运动区域和火焰颜色区域来确定初级疑似火焰区域;然后对初级疑似区域和非疑似区域制定不同的背景建模策略来得到运动前景;最后由运动区域和高亮区域得到最终的火焰前景。与4种已有的火焰前景提取算法的对比实验表明,该算法在复杂背景下的火焰前景提取准确率为96.2%,远高于现有算法;能适应不同类型的复杂背景,并且满足实时性要求。

Flame foreground extraction underthe interference of intense light

Flame foreground extraction is an important step in video-based fire detection algorithms, and it is the basis of following flame feature recognition algorithms. Given the fact that existing flame foreground extraction algorithms cannot extract flame foreground accurately under the interference of intense light or when the background color is similar to the flame, we propose a new algorithm to extract fire foreground. Firstly, the algorithm determines the primary suspected region by calculating the momentary motion region and the fire colored region. Secondly, we obtain the moving foreground region by different background subtraction methods according to the primary suspected region. Finally, we get the fire foreground region according to the moving foreground region and the fire colored region. Experimental results show that compared with four existing flame foreground extraction methods, the proposed algorithm has a much higher accuracy rate (100%). The proposed method can adapt to different complicated backgrounds and meet real-time requirement.