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Image Processing-based Fire Detection System using Statistic Color Model

机译:基于图像处理的火灾探测系统使用统计颜色模型

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Most of fire detection system used the heuristic fixed threshold values in their specific methods. However, input images may be changed, in general, so the heuristic fixed threshold values used in the fire detection systems might be modified on a case by case basis. In this paper, an automatic fire detection system without the heuristic fixed threshold values was studied. We presented an automatic method using the statistical color model and the binary background mask. We did the experiment using 600 frames from 6 typical different fire video clips. As the experimental results the proposed method showed a good performance of about average 85% detection rate without false positive, compared with the other methods with the heuristic fixed threshold values.
机译:大多数火灾检测系统使用其特定方法中的启发式固定阈值。然而,通常可以改变输入图像,因此在逐个情况下可以修改火灾检测系统中使用的启发式固定阈值。本文研究了没有启发式固定阈值的自动火灾检测系统。我们使用统计颜色模型和二进制背景掩模提出了一种自动方法。我们使用600帧从6个典型的不同火视频剪辑进行了实验。作为实验结果,该方法显示出良好的性能,比具有启发式固定阈值的其他方法相比,没有假阳性的良好性能。

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