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    吴梦宇, 罗琴娟, 韩摇宁. 基于多运动特征的森林火灾烟雾图像识别算法[J]. 北京林业大学学报, 2013, 35(3): 154-158.
    引用本文: 吴梦宇, 罗琴娟, 韩摇宁. 基于多运动特征的森林火灾烟雾图像识别算法[J]. 北京林业大学学报, 2013, 35(3): 154-158.
    WU Meng-yu, LUO Qin-juan, HAN Ning.. A smoke detection algorithm based on multiple motion features.[J]. Journal of Beijing Forestry University, 2013, 35(3): 154-158.
    Citation: WU Meng-yu, LUO Qin-juan, HAN Ning.. A smoke detection algorithm based on multiple motion features.[J]. Journal of Beijing Forestry University, 2013, 35(3): 154-158.

    基于多运动特征的森林火灾烟雾图像识别算法

    A smoke detection algorithm based on multiple motion features.

    • 摘要: 为甄别林火烟雾与大气云雾,提出了基于多种运动特征判据的视频烟雾图像检测算法。首先利用烟雾自身 的光学动态特征———光流方向性、相关性、扩散性,分别对连续帧包含烟云的可疑区域进行图像特征标志判别;再 经数据融合算法有效区分林火烟雾与大气云雾,克服了依靠单一图像特征检测烟雾的不足。结果表明,光流方向 性、相关性、扩散性判别相结合的识别算法能提高森林火灾视频图像的有效识别率。

       

      Abstract: A smoke detection algorithm combined of multiple motion features was presented. The main purpose of this paper was to separate the smoke-resembling natural phenomena such as clouds, cloud shadows and dust from real smoke. The optical flow property, correlation property based on discrete wavelet transform and diffusion property were matched together to make discrimination. At last, a data weighted fusion algorithm based on statistics theory was applied into smoke detection. Experimental results showed that, compared with the algorithm of detecting smoke using single property, the proposed method can improve the accuracy of smoke detection.

       

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