基于神经网络的火灾图像特征融合算法

针对传统火灾探测技术存在的不稳定、误判率高等缺点,着重分析了室内火灾图像与常见干扰光源图像的特点,提出用火焰区域面积变化、质心位置、尖角数、圆形度等信息作为火灾判据,并用模糊神经网络对以上特征参数进行数据融合,作出火灾判断。实验结果表明,基于模糊神经网络的信息融合算法能够有效识别出火灾火焰,提高了识别的准确率。

Fire Image Date Fusion Based on Neural Network

Considering the unstability and high erroneous recognition with traditional methods for fire detection, this paper analyzes the characteristics of fire image and the familiar interference light source. Four criteria have been mentioned: the area increases gradually, the centroid changes random, the taper angles and the circularity. Fuzzy neural network(NN) is used in information fusion to distinguish the fire. Experiments show that Fuzzy neural network fire detection algorithm can distinguish the fire flame effectively and improve accuracy.