期刊文献+

基于数字图像处理的大范围区域的火焰识别 被引量:2

Flame Recognition Based on Digital Image Processing of Large Areas
在线阅读 下载PDF
导出
摘要 传统的检测火焰的方法并不能发挥很好的作用,近些年,随着计算机以及基于视频图像序列处理的数字图像处理技术的发展,基于视觉火焰检测技术在大范围空间具有十分实用的价值。通过数字彩色CCD摄像机获得连续的图片,我们可以通过图像利用数字图像处理的算法来获得所感兴趣区域的形状特征,静态动态特征以及颜色信息,从而来判断是否发生了火灾。将摄像系统装配在所需检测的位置从而达到对检测区域自动防火的功能。简便的算法也可以减少对数据处理的时间。实验的结果说明了我们的方法可以准确地确认火焰。 In recent years,with the development of computer and digital image processing technology based on video image sequence processing,flame detection technology based on vision has a very practical value in wide range space.With the continuous images obtained by a digital color CCD camera,digital image processing algorithms to obtain the shape characteristics,the static and dynamic characteristics,and color information of the interesting region,so as to determine whether there is a fire.Assemble a camera system in the required location to achieve at the function of automatic fire detection of the tested area.Simple algorithm can also reduce data processing time.
出处 《工业控制计算机》 2012年第8期79-80,共2页 Industrial Control Computer
关键词 火焰检测 数字图像处理 火焰特征 图像分割 边缘提取 flame detection digital image processing flame characteristics image segmentation edge extraction
  • 相关文献

参考文献2

二级参考文献13

  • 1伍茜,沈季胜,刘震涛,俞小莉.动态图像差分法在热裂纹提取上的应用[J].兵工学报,2006,27(1):154-158. 被引量:2
  • 2BALDINI G, CAMPADELLI P. Combustion Analysis by Image Processing of Premixed Flames. Vancouver, BC, Canada,2000.
  • 3HANTON K, BUTAVICIUS M. improving infrared images for standoff object detection. Information Technology Interfaces, 2009:641 - 646.
  • 4HUA L, SHI-CHAO Z. A near infrared imaging detection system based on davinci platform. Beijing, China,2009.
  • 5YAMAGUCHI T, GRATI'AN K. A practical fiber optic air-ratio sensor operating by flame color detection. Review of Scientific Instruments, 1997,68 ( 1 ) : 197 - 202.
  • 6LI H, CHANG S. Color Context Analysis based Efficient Real -time Flame Detection Algorithm. Singapore,2008.
  • 7DU Feng, WENKANG S. infrared image segmentation with 2 - D maximum entropy method based on particle swarm optimization (PSO). Pattern Recognition Letters,2005,26 (5) :597 - 603.
  • 8Kyaw M M, Ahmed S K. Shape-Based Sorting of Agricultural Produce Using support vector machines in a MATLABSIMULINK Environment. Kuala Lumpur,2009.
  • 9蔡梅艳,吴庆宪,姜长生.改进Otsu法的目标图像分割[J].电光与控制,2007,14(6):118-119. 被引量:48
  • 10甘新胜,赵书斌.基于背景差的运动目标检测方法比较分析[J].指挥控制与仿真,2008,30(3):45-50. 被引量:28

共引文献12

同被引文献20

引证文献2

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部