Fire Detection Algorithms Using Multimodal ... - Bilkent University

Chapter 6Wildfire DetectionIn this chapter, a computer vision based algorithm for wildfire detection is developed.The main detection algorithm is composed of four sub-algorithms detecting(i) slow moving objects, (ii) smoke-colored regions, (iii) rising regions, and(iv) shadows. Each sub-algorithm yields its own decision as a zero-mean realnumber, representing the confidence level of that particular sub-algorithm. Confidencevalues are linearly combined with weights determined according to a novelactive fusion method based on the least-mean-square (LMS) algorithm which isa widely used technique in adaptive filtering. Weights are updated on-line usingthe LMS method in the training (learning) stage. The error function of the LMSbased training process is defined as the difference between the weighted sum ofdecision values and the decision of an oracle, who is the security guard of theforest look-out tower. Simulation results are presented.6.1 Related WorkManned lookout posts are widely available in forests all around the world to detectwild fires. Surveillance cameras can be placed on to these surveillance towers tomonitor the surrounding forestal area for possible wild fires. Furthermore, theycan be used to monitor the progress of the fire from remote centers.81