期刊文献+

视频监控系统在火灾报警中的应用 被引量:6

Application of video surveillance system in fire alarm
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摘要 针对当前火灾检测、监控能力薄弱的现状,提出了一种用于视频监控系统中对火灾进行有效检测和报警的方法,该方法首先利用DirectShow与FFMPET相结合的方式把视频帧从播放的视频流中提取出来,并保存为视频帧图片文件,接着利用ASIFT算法对得到的视频帧图片与原始静态图片进行特征提取和特征匹配,然后对匹配成功的匹配点进行归一化处理,最后,通过系统对视频流进行自动分帧处理与判别,对超过设定阈值的进行报警,实验结果表明,该方法实现成本较低,操作简单、快速、有效,灵敏度高,可降低误报、漏报,适用于对重点无人职守区域进行火灾检测和报警的监控系统。 This paper presents a fire detection and alarm method for video surveillance system. Using the DirectShow and FFMPET combination method to extract video frame pictures from the video stream and save it as a video frame file. Then we can perform feature extraction and feature matching between the video frame images and the original static picture using ASIFF algorithm. Then matching point is nor- malized. Finally, surveillance system alarms if the set threshold is exceeded. The result show that the method proposed in this paper is simple with high speed and effect. The false alarm can be reduced. It can be used in unattended area of video surveillance environment for detecting fire and alarming.
作者 来望银
出处 《西安科技大学学报》 CAS 2013年第4期400-403,共4页 Journal of Xi’an University of Science and Technology
关键词 视频监控 视频分帧 火灾检测 火灾报警 ASIFT video surveillance system video framing fire detection fire alarm ASIFT
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参考文献12

  • 1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):389-393. 被引量:5
  • 2Frederic P, Miller Agnes F, Vandome John McBrewster. Directshow : open source, DirectX Media Objects, Media Foundation, DirectX plugin, DirectX video acceleration, multimedia framework, application programming interface, microsoft, software de- veloper [ M ]. Alpha Press, 2009.
  • 3David G, Lowe. Object recognition from local scale-invariant features [ J ]. International Conference on Computer Vision, 1999, 55(4) :1 150-1 157.
  • 4David G, Lowe. Distinctive image features from scale-invariant key-points [ J ]. International Journal of Computer Vision,2004, 60(2) :91 - 110.
  • 5David G, Lowe. Local feature view clustering for 3D object recognition [ C ]//IEEE Conference on Computer Vision and Pat- tern Recognition, Kauai, Hawaii,2011,12 ( 8 ) : 682 - 688.
  • 6李海涛,吴培良,孔令富.目标主色集结合SIFT的彩色目标快速识别[J].计算机科学,2009,36(12):257-258. 被引量:6
  • 7YAN Ke, Rahul Sukthankar. PCA-SIFT: a more distinctive representation for local Image descriptors [ J ]. Proceedings of the Conference on Computer Vision and Pattern Recognition, Washington, USA ,2004,23 (10) :511 - 517.
  • 8LI Yan-fang, WANG Ya-ning, HUANG Wen-qing, et al. Automatic image stitching using SIFT[ C ]//ICALIP 2008 -2008 In- ternational Conference on Audio, Language and Image Processing, Proceedings ,2008,27 (32) :568 -571.
  • 9Morel J M, Yu G S, ASIFF. A new framework for fully affine invariant image comparison [ J ]. SIAM Journal on Imaging Sci- ences ,2009,2 (2) :438 - 469.
  • 10Morel 3 M ,Yu G S. Is SIFT scale invariant? [ J]. Inverse Problems and Imaging,2011,5( 1 ) :1 -22.

二级参考文献19

  • 1蒋爱平,王祁.分数布朗运动在X线图像边缘提取中的应用[J].控制工程,2005,12(5):476-479. 被引量:3
  • 2Mikolajezyk K,Schmid C. A performance evaluation of local descriptors[A]//Proeeedings of IEEE International Conference on Computer Vision and Pattern Recognition[C]. Madison, IEEE, 2003 : 1403-1410.
  • 3Lowe D. Object recognition from local scale - invariant features [A]//Proceedings oS International Conference on Computer Vision[C]. Vancouver, ICCV, 1999: 1150-1157.
  • 4Lowe D. Distinctive image features from scale - invariant key - points[J]. International Journal of Computer Vision, 2004, 60 (2):91-110.
  • 5Ke Y,Sukthankar R. PCA-SIFT: A More Distinctive Representation for Local Image Descriptors [A]// Proceedings of the IEEE Computer Society Conference[C]. Washington DC, IEEE, 2004:511-517.
  • 6Abdel-Hakim E, Farag A. CSIFT: A SIFT Descriptor with Color Invariant Characteristics[A]//Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition[C]. New York, IEEE, 2006:1978-1983.
  • 7Bosch A, Zisserman A, Munoz X. Scene classification via pLSA [A],//Proceedings of the European Conference on Computer Vision[C]. Graz, ECCV, 2006 : 517-530.
  • 8Stauffer C, Grimson WEL. Learning patterns of activity using real-time tracking[ J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22 (8) :747 - 757.
  • 9Turgay Celik, Hasan Demirel, Huseyin Ozkaramanli. Fire detection using statistical color model in video sequences [ J ]. Journal of Visual Communication & Image Representation.
  • 10Celik T, Demirel H. Fire detection in video sequences using a generic color model [ J ]. Fire Safety Journal ,2009,44 (2) :147 - 158.

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