公开(公告)号：US08432451B2

公开(公告)日：2013-04-30

申请号：US12418238

申请日：2009-04-03

申请人： Ahmet Enis Cetin ,  Behcet Ugur Toreyin

发明人： Ahmet Enis Cetin ,  Behcet Ugur Toreyin

IPC分类号： H04N5/33 ,  H04N5/225

CPC分类号： G08B21/12 ,  G06K9/6288 ,  G06T7/262

摘要： A video based method to detect volatile organic compounds (VOC) leaking out of components used in chemical processes in petrochemical refineries. Leaking VOC plume from a damaged component causes edges present in image frames to loose their sharpness, leading to a decrease in the high frequency content of the image. Analysis of image sequence frequency data from visible and infrared cameras enable detection of VOC plumes in real-time. Analysis techniques using adaptive background subtraction, sub-band analysis, threshold adaptation, and Markov modeling are described.

摘要翻译： 一种基于视频的方法来检测挥发性有机化合物（VOC）泄漏出用于石油化工炼油厂化学过程的组分。 从损坏的组件泄漏VOC羽流导致图像帧中存在的边缘松动其锐度，导致图像的高频内容减少。 对来自可见光和红外摄像机的图像序列频率数据的分析能够实时检测VOC羽流。 描述了使用自适应背景减法，子带分析，阈值适应和马尔科夫建模的分析技术。

公开(公告)号：US09047515B2

公开(公告)日：2015-06-02

申请号：US13825003

申请日：2010-09-13

申请人： Ahmet Enis Cetin ,  Osman Gunay

发明人： Ahmet Enis Cetin ,  Osman Gunay

IPC分类号： G06K9/00 ,  G06K9/40 ,  G08B17/00 ,  G08B17/12 ,  G06T7/00 ,  G06T7/20

CPC分类号： G06K9/00657 ,  G06K9/00147 ,  G06T7/12 ,  G06T7/254 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/30232 ,  G08B17/005 ,  G08B17/125

摘要： Wildfires are detected by controlling image scanning within the viewing range of a video camera to generate digital images that are analyzed to detect gray colored regions, and then to determine whether a detected gray colored region is smooth. Further analysis to determine movement in a gray colored smooth region uses a past image which is within a slow moving time range, as determined by a strategy for controlling the image scanning. Additional analysis connects a candidate region to a land portion of the image, and a support vector machine is applied to a covariance matrix of the candidate region to determine whether the region shows smoke from a wildfire.

摘要翻译： 通过在摄像机的观看范围内控制图像扫描来检测野火，以产生被分析以检测灰色区域的数字图像，然后确定检测到的灰色区域是否平滑。 用于确定灰色平滑区域中的移动的进一步分析使用由用于控制图像扫描的策略确定的在慢的移动时间范围内的过去图像。 附加分析将候选区域连接到图像的陆地部分，并且将支持向量机应用于候选区域的协方差矩阵，以确定该区域是否显示来自野火的烟雾。

公开(公告)号：US20130286213A1

公开(公告)日：2013-10-31

申请号：US13825005

申请日：2011-01-19

申请人： Ahmet Enis Cetin ,  Beheet Ugur Toreyin

发明人： Ahmet Enis Cetin ,  Beheet Ugur Toreyin

IPC分类号： H04N5/33

CPC分类号： H04N5/332 ,  G01M3/002 ,  G01M3/38 ,  G01N21/3504 ,  G06T7/001 ,  G06T7/254 ,  G06T2207/10048 ,  H04N5/33

摘要： A video based method to detect volatile organic compounds (VOC) leaking out of components used in chemical processes in petrochemical refineries. Leaking VOC plume from a damaged component has distinctive properties that can be detected in realtime by an analysis of images from a combination of infrared and optical cameras. Particular VOC vapors have unique absorption bands, which allow these vapors to be detected and distinguished. A method of comparative analysis of images from a suitable combination of cameras, each covering a range in the IR or visible spectrum, is described. VOC vapors also cause the edges present in image frames to loose their sharpness, leading to a decrease in the high frequency content of the image. Analysis of image sequence frequency data from visible and infrared cameras enable detection of VOC plumes. Analysis techniques using adaptive background subtraction, sub-band analysis, threshold adaptation, and Markov modeling are described.

摘要翻译： 一种基于视频的方法来检测挥发性有机化合物（VOC）泄漏出用于石油化工炼油厂化学过程的组分。 从损坏的组件泄漏VOC羽流具有独特的属性，可以通过红外和光学相机的组合分析实时检测。 特定的VOC蒸气具有独特的吸收带，可以检测和区分这些蒸气。 描述了一种从适当组合的照相机（其覆盖IR或可见光谱范围）的图像进行比较分析的方法。 VOC蒸汽也会导致图像帧中存在的边缘消失其清晰度，导致图像的高频内容降低。 从可见光和红外摄像机分析图像序列频率数据可以检测VOC羽流。 描述了使用自适应背景减法，子带分析，阈值适应和马尔科夫建模的分析技术。