Fire Detection Algorithms Using Multimodal ... - Bilkent University

CHAPTER 6. WILDFIRE DETECTION 88that of the previous frame, then S2 is attained and this means that the regionmoves-down. No change in the row value corresponds to S3.Figure 6.2: Markov model λ 1 corresponding to wildfire smoke (left) and theMarkov model λ 2 of clouds (right). Transition probabilities a ij and b ij are estimatedoff-line.A slow moving region is classified as a rising region when the probability ofobtaining the observed feature signal F = f(n) given the probability model λ 1is greater than the probability of obtaining the observed feature signal F = f(n)given the probability model λ 2 , i.e., when the upper-most pixel belonging to aslow moving region tends to exhibit a rising characteristic:p 1 = P (F |λ 1 ) > p 2 = P (F |λ 2 ) (6.4)where F is the observed feature signal, λ 1 and λ 2 represent the Markov modelsfor wildfire smoke and clouds, respectively.As the probability p 1 (p 2 ) gets a larger value than p 2 (p 1 ), the confidence levelof this sub-algorithm increases (decreases).Therefore, the zero-mean decisionfunction D 3 (x, n) is determined by the normalized difference of these probabilities:D 3 (x, n) = p 1 − p 2p 1 + p 2(6.5)