基于飞行时间深度图像变化率的火焰识别方法

Identification of fire flame based on variation rate of time-of-flight-depth-map method

为开发飞行时间算法在火灾探测中的应用,简化算法,提高检测速率和准确性,根据飞行时间法,结合火焰的深度图特征,设计了基于深度图像变化率的火焰识别算法。以三维深度相机为主要图像捕获设备,进行了多组火焰识别实验,包括正庚烷火焰、乙醇火焰、纸张火焰、灯光干扰、行人干扰实验,对捕获的图像进行了处理与计算,提出了识别火焰的简化算法和火焰像素估计模型。采用该方法分析了火焰深度图特征,火焰识别结果图像的频谱图特征、集中度特征以及面积变化特征。研究结果表明,采用文中提出的算法的实验识准率大于91.5%,误识率小于3.8%,能有效识别火焰。

In order to develop the application of time-of-flight algorithm in fire detection and simplify the algorithm to improve detection rate and accuracy, according to the time-of-flight-depth-map method, considering with the characteristics of depth map of fire flame, fire flame identification algorithm based on variation rate of time-of-flight-depth-map was designed. Several groups of fire flame identification experiments, including n-heptane flame, ethanol flame, paper flame, lamplight interference and pedestrian interference test, were carried out with 3-D depth camera acted as main equipment. The captured maps were processed and computed. A simplified algorithm was proposed for fire flame identification which was used to analyze the characteristics of depth map, frequency spectrogram, concentration ratio and area fluctuation of fire flame. The results indicate that the identification precision rate is greater than 91.5%, and the misrecognition rate is less than 3.8%. Fire flame could be efficiently identified with this algorithm.