Industry Academic Cooperation Foundation Keimyung University

Joon Young Kwak

ByoungChul Ko

JaeYeal Nam

A forest fire smoke detection method using random forest classification is provided. In the method, a first reference value is set. For consecutively captured frames, images between the frames are compared, each block, in which a number of pixels, motions of which have been identified, is equal to or greater than the first reference value, is set as a candidate block, and a keyframe is selected. The selected keyframe is compared with at least one frame previous to the keyframe and then a plurality of feature vectors are extracted from the candidate blocks. The extracted feature vectors are learned using different random forest algorithms. Probabilities output to terminal nodes for classes are accumulated, and two first cumulative probability histograms are generated. The two first cumulative probability histograms are averaged, and then a second cumulative probability histogram is generated. A detected state of each candidate block is determined.

Growing community of inventors

Daegu, South Korea

Joon Young Kwak