基于视频图像的含硫矿自燃探测研究
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摘要
阐述了含硫矿开采过程自燃的危害,以及传统火灾探测方法的局限。研究了基于视频图像的含硫矿自燃探测方案,提出了一种背景自动更新目标提取法,以及改进的支持向量机分类识别算法。实验数据表明,该研究提高了分类速度和识别准确率。
This thesis expounds the hazard of spontaneous combustion during the mining process of sulfur ores and the limitation of traditional fire detection method. A image and video based scheme for spontaneous combustion detection of sulfur ores is studied,and a background auto-updated object extraction method is proposed. A improved vector machine classification algorithm is put forward as well in this thesis. The experimental data represents that this study improves the speed of classification and the accuracy rate of recognition.
This thesis expounds the hazard of spontaneous combustion during the mining process of sulfur ores and the limitation of traditional fire detection method. A image and video based scheme for spontaneous combustion detection of sulfur ores is studied,and a background auto-updated object extraction method is proposed. A improved vector machine classification algorithm is put forward as well in this thesis. The experimental data represents that this study improves the speed of classification and the accuracy rate of recognition.
引文
[1]黄金星.含硫矿石自燃机理及其危险性预测技术研究[D].西安:西安科技大学,2010.
[2]吴超,孟廷让.高硫矿井内因火灾防治理论与技术[M].北京:冶金工业出版社,1995.
[3]王媛彬,马宪民.基于图像型的煤矿早期外因火灾预测及识别方法研究[J].西安科技大学学报,2012,32(3):289-293.
[4]严云洋,高尚兵,郭志波.基于视频图像的火灾自动检测[J].计算机应用研究,2008,25(4):1075-1078.
[5]齐怀琴,徐刚,王娜.基于视频图像的森林火灾识别算法研究[J].电视技术,2010,34(9):116-118.
[6]范华忠,张伯虎,冯艳.图像处理技术在火焰目标提取中的应用[J].电光与控制,2006,13(1):99-104.
[7]黄玲,齐保谦,胡波.基于图像连通区域面积的成捆棒材自动计数方法[J].工矿自动化,2012(5):77-79.
[8]马宗方,咏梅,潘泉,等.快速支持向量机的图像型火灾探测算法[J].计算机应用研究,2010,27(10):3986-3988.
[9]高恒振,万建伟,粘永健,等.组合核函数支持向量机高光谱图像融合分类[J].光学精密工程,2011,19(4):878-883.
[10]MATHIEU F,BENEDIKTSSON J A,CHANUSSOT J,et al.Spectral and spatial classification of hyperspectral data using SVMs and morphologicalprofiles[J].IEEE Trans.Geosci.Remote Sens.,2008,46(11):3804-3814.
[11]彭育兴.基于支持向量机的空中目标识别技术研究[D].长沙:国防科学技术大学,2009.
[2]吴超,孟廷让.高硫矿井内因火灾防治理论与技术[M].北京:冶金工业出版社,1995.
[3]王媛彬,马宪民.基于图像型的煤矿早期外因火灾预测及识别方法研究[J].西安科技大学学报,2012,32(3):289-293.
[4]严云洋,高尚兵,郭志波.基于视频图像的火灾自动检测[J].计算机应用研究,2008,25(4):1075-1078.
[5]齐怀琴,徐刚,王娜.基于视频图像的森林火灾识别算法研究[J].电视技术,2010,34(9):116-118.
[6]范华忠,张伯虎,冯艳.图像处理技术在火焰目标提取中的应用[J].电光与控制,2006,13(1):99-104.
[7]黄玲,齐保谦,胡波.基于图像连通区域面积的成捆棒材自动计数方法[J].工矿自动化,2012(5):77-79.
[8]马宗方,咏梅,潘泉,等.快速支持向量机的图像型火灾探测算法[J].计算机应用研究,2010,27(10):3986-3988.
[9]高恒振,万建伟,粘永健,等.组合核函数支持向量机高光谱图像融合分类[J].光学精密工程,2011,19(4):878-883.
[10]MATHIEU F,BENEDIKTSSON J A,CHANUSSOT J,et al.Spectral and spatial classification of hyperspectral data using SVMs and morphologicalprofiles[J].IEEE Trans.Geosci.Remote Sens.,2008,46(11):3804-3814.
[11]彭育兴.基于支持向量机的空中目标识别技术研究[D].长沙:国防科学技术大学,2009.