Graduate School, ESIME-Culhuacan, National Polytechnic Institute, Av. Santa Ana no. 1000, Col. San Francisco Culhuacan, Mexico D.F., 04430, Mexico.
Sensors (Basel). 2012;12(5):5670-86. doi: 10.3390/s120505670. Epub 2012 May 3.
The presence of smoke is the first symptom of fire; therefore to achieve early fire detection, accurate and quick estimation of the presence of smoke is very important. In this paper we propose an algorithm to detect the presence of smoke using video sequences captured by Internet Protocol (IP) cameras, in which important features of smoke, such as color, motion and growth properties are employed. For an efficient smoke detection in the IP camera platform, a detection algorithm must operate directly in the Discrete Cosine Transform (DCT) domain to reduce computational cost, avoiding a complete decoding process required for algorithms that operate in spatial domain. In the proposed algorithm the DCT Inter-transformation technique is used to increase the detection accuracy without inverse DCT operation. In the proposed scheme, firstly the candidate smoke regions are estimated using motion and color smoke properties; next using morphological operations the noise is reduced. Finally the growth properties of the candidate smoke regions are furthermore analyzed through time using the connected component labeling technique. Evaluation results show that a feasible smoke detection method with false negative and false positive error rates approximately equal to 4% and 2%, respectively, is obtained.
烟雾的存在是火灾的第一个症状；因此，要实现早期火灾探测，准确快速地估计烟雾的存在非常重要。在本文中，我们提出了一种使用 IP 摄像机捕获的视频序列检测烟雾存在的算法，其中利用了烟雾的重要特征，如颜色、运动和增长特性。为了在 IP 摄像机平台上实现有效的烟雾检测，检测算法必须直接在离散余弦变换（DCT）域中运行，以降低计算成本，避免在空间域中运行的算法所需的完整解码过程。在提出的算法中，使用 DCT 互变换技术来提高检测精度，而无需进行逆 DCT 操作。在提出的方案中，首先使用运动和颜色烟雾特性估计候选烟雾区域；接下来使用形态学操作减少噪声。最后，通过使用连通分量标记技术，通过时间进一步分析候选烟雾区域的增长特性。评估结果表明，得到了一种可行的烟雾检测方法，其假阴性和假阳性错误率分别约为 4%和 2%。
