| 煤矿井下图像型早期火灾探测 |
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| 引用本文： | 王媛彬,马宪民.煤矿井下图像型早期火灾探测[J].辽宁工程技术大学学报(自然科学版),2011,30(5):713-716. |
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| 作者姓名： | 王媛彬 马宪民 |
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| 作者单位： | 西安科技大学,电控学院,陕西,西安,710054 |
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| 基金项目： | 国家自然科学基金资助项目(50977077); 陕西省教育厅科研计划资助项目(11Jk0908); 西安科技大学培育基金(2010010) |
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| 摘 要： | 针对煤矿井下传统火灾探测方法的不足,提出了一种基于图像型的火灾探测方法,阐述了对所获取的红外图像进行预处理、特征提取和火灾识别的过程。根据早期火灾的特点,通过提取图像序列中多个参数的火灾信息,并将量化后的火灾特征值输入支持向量机,对支持向量机进行分类器训练,再利用训练好的分类器对火灾和干扰物进行分类识别。实验结果表明:该方法探测正确率高,误判率低,抗干扰能力强,对于小样本的非线性分类问题效果较好。该研究成果对煤矿外因火灾的预防具有一定实际意义。
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| 关 键 词： | 煤矿井下 早期探测 图像 特征提取 火灾识别 火灾信息 融合 SVM |
Early fire detection based on image in underground coal mine |
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| WANG Yuanbin,MA Xianmin.Early fire detection based on image in underground coal mine[J].Journal of Liaoning Technical University (Natural Science Edition),2011,30(5):713-716. |
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| Authors: | WANG Yuanbin MA Xianmin |
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| Institution: | WANG Yuanbin,MA Xianmin(School of Electrical & Control Engineering,Xi'an University of Science & Technology,Xi'an 710054,China) |
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| Abstract: | To overcome the shortcomings in traditional fire detection method in underground coal mine,a novel approach based on digital image processing and pattern recognition is proposed in this paper.In addition,the processes of infrared image obtaining,preprocessing and feature extraction are discussed in detail.According to the fire features at early stage,the fire information of multi-parameters is extracted from image sequence.Subsequently,the characteristics values are quantified and input into Support Vector ... |
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| Keywords: | coal mine early detection image feature exaction fire recognition fire information fusion SVM |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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