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FOREST FIRE SMOKE DETECTION METHOD USING RANDOM FOREST CLASSIFICATION

机译:基于随机森林分类的​​林火烟气检测方法

摘要

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.
机译:提供一种使用随机森林分类的​​森林火灾烟气检测方法。在该方法中,设置第一参考值。对于连续捕获的帧,比较帧之间的图像,将每个块(其中已识别其运动的像素数量等于或大于第一参考值)设置为候选块,并设置关键帧被选中。将所选择的关键帧与该关键帧之前的至少一帧进行比较,然后从候选块中提取多个特征向量。使用不同的随机森林算法学习提取的特征向量。累积输出到终端节点的类别的概率,并生成两个第一累积概率直方图。对两个第一累积概率直方图求平均,然后生成第二累积概率直方图。确定每个候选块的检测状态。

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