Forest Fire Image Intelligent Recognition Under Sea Computing Model


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Abstract


The methods of forest fire prevention still couldn't achieve high accuracy and low time-consuming at the same time. To the image features of forest fire, this article discussed the significance of forest fire prevention combining sea computing, studied the forest fire image intelligent recognition under sea computing model and proposed the forest fire recognition algorithm based on sea computing. We used Qt/Embedded to design the algorithm according to the characteristics of the sensor node, and then completed the judgment of color and region by this algorithm through additive color model and Sobel operator. Finally, the results were automatically fed back to the sink node. The experiments showed that, this algorithm not only completed the instant detection and recognition of forest fire, but also synchronously achieved higher accuracy rate and lower time-consuming compared with the traditional methods.
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Keywords


Sea Computing Model; Qt/Embedded; Additive Color Model; Sobel Operator

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References


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