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Forest Smoke Detection Using CCD Camera and Spatial-temporal Variation of Smoke Visual Patterns

机译:CCD摄像机检测森林烟雾及烟雾视觉图案的时空变化

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This paper proposes a new forest smoke detection method using spatial-temporal visual features extracted from camera images and a pattern classification technique. First, moving regions are detected by analyzing the frame difference between two consecutive key frames. Since smoke regions generally have a similar color, simple texture, and upward motion, the intensity, wavelet coefficients, and motion orientation are extracted as visual features. In addition, random forests are constructed using training data and then used for smoke verification process with four smoke classes. The proposed algorithm is successfully applied to various forest smoke videos and shows a better detection performance when compared with other methods.
机译:本文提出了一种新的森林烟雾检测方法,该方法利用了从相机图像中提取的时空视觉特征和模式分类技术。首先,通过分析两个连续关键帧之间的帧差来检测运动区域。由于烟雾区域通常具有相似的颜色,简单的纹理和向上运动,因此将强度,小波系数和运动方向提取为视觉特征。此外,使用训练数据构建随机森林,然后将其用于具有四个烟雾类别的烟雾验证过程。所提出的算法已成功应用于各种森林烟雾视频,与其他方法相比具有更好的检测性能。

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