In order to improve accuracy and rapidity of fire detection

a smog detection algorithm based on texture features and optical flow vector of contour is proposed. On one hand

to obtain more comprehensive texture feature

image pyramid is constructed

a new method combines local binary pattern（ LBP） with LBP based on variance（ LBPV） are used to extract texture feature of different level of the image pyramid. On the other hand

due to special turbulence characteristics of smoke movement

its moving directions are with a certain consistency

improve the method of analysis on all suspicious area

optical flow vector analysis is carried out only on suspicious area contour

which greatly reduces computational complexity. These features are input to SVM for recognition.‘Still—Still—Moving’approach is used

experimental results prove that it can timely and accurately gives alarm and it has high reliability.