Fire detection based on brightness and color distribution of fire edge regions
基于亮度与火焰区域边缘颜色分布的火焰检测*

In order to improve the situation which most fire detection methods are not strong to adapt to a variety of environment, this paper proposed a new fire detection method based on the brightness and color distribution of the fire edge regions. It calculated the color distribution characteristic matrix of the fire edge regions using reconstruction, binary morphological and boundary-tracing algorithms. Then processed the color distribution matrix with PCA algorithm. And bound BP neural network input vectors by covariance Eigen value of PCA components. Through that, conducted fire detection accurately. The experiment shows that this algorithm is simple, and can identify fire image accurately against a variety of backgrounds.