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中文摘要：
针对传统森林防火方法中耗能低效的问题，讨论了海计算模式下森林防火的意义，并提出了海计算模式下森林火焰识别算法的实现．首先根据感知端的特点使用Qt／Embedded设计，再依据森林火焰的特点使用24比特加色模型和Sobel算子实现色彩和区域判定，最后把结果反馈到汇聚节点．该算法能自动对视频捕获的图像进行分析计算并能自动反馈结果，在传感端就完成了火情判别．经实验验证，相比传统的森林防火方法，该算法不仅实现了森林火灾的即时检测和识别，同时也实现了高准确率和低耗能．
英文摘要：
To the problem of low efficiency and high energy consumption for the traditional forest fire prevention methods, this article discussed the significance of forest fire prevention based on Sea computing, and put forward the implementation of forest fire recognition algorithm based on Sea computing. Firstly, used Qt/Embedded to design according to the characteristics of the sensor node. Then, used 24-bits additive color model and Sobel operator to complete the decision of color and region based on the features of forest fire. Finally, the results were fed back to the sink node. This algorithm could automatically analysis image captured by camera and complete the decision of fire in sensor node. The experiments showed that, compared to the traditional methods of forest fire prevention, this algorithm not only completed the instant detection and recognition of forest fire, but also achieved high accuracy rate and low time-consuming at the same time.
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