长期以来,森林火灾检测一直都是世界范围内的一个重要研究课题,对于保护地球环境及人类安全都有重要意义。基于视频监控的火灾检测对于实时性和正确性要求很高,而传感式探测器和传统图像型探测器不能满足要求。提出了一种基于动态纹理特征分析的新型图像型火灾检测算法,对于森林这样的复杂大空间场景尤为适用。通过对CCD摄像机拍摄的视频图像,建立线性动力系统(LDS)模型,分析其动态纹理特征,最后利用Adaboost分类器判断火灾是否存在。实验结果表明,此算法能够达到95%的检测准确率,且具有较好的应用前景。

For a long time, forest fire detection is one of the most important research areas all over the world. It is crucial for protecting the earth and human survival. Real-time and accuracy is the essential need in surveillance system, especially in forest fire detection. However, the traditional sensor-based and conventional image-based fire detection approaches can not satisfy the needs. To achieve an effective detection of such fire, an image-based forest fire detection algorithm based on dynamic texture analysis is proposed. The first step is to establish Linear Dynamic System(LDS)model on the video image sequences captured by CCD camera, then analysis the dynamic textures, and finally determine the existence of the fire by Adaboost classifier. Experimental results demonstrate that the rate of accuracy of the proposed algorithm can achieve 95%. It is efficient and robust with good application prospects.