Forest fires are frequent natural disasters.It is necessary to explore advanced means to monitor,recognize and locate forest fires so as to establish a scientific system for the early detection,real-time positioning a...Forest fires are frequent natural disasters.It is necessary to explore advanced means to monitor,recognize and locate forest fires so as to establish a scientific system for the early detection,real-time positioning and quick fighting of forest fires.This paper mainly expounds methods and algorithms for improving accuracy and removing uncertainty in image-based forest fire recognition and spatial positioning.Firstly,we discuss a method of forest fire recognition in visible-light imagery.There are four aspects to improve accuracy and remove uncertainty in fire recognition:(1)eliminating factors of interference such as road and sky with high brightness,red leaves,other colored objects and objects that are lit up at night,(2)excluding imaging for specific periods and azimuth angles for which interference phenomena repeatedly occur,(3)improving the thresholding method for determining the flame border in image processing by adjusting the threshold to the season,weather and region,and (4)integrating the visible-light image method with infrared image technology.Secondly,we examine infrared-image-based methods and approaches of improving the accuracy of forest fire recognition by combining the spectrum threshold with an object feature value such as the normalized difference vegetation index and excluding factors of disturbance such as interference signals,extreme weather and high-temperature animals.Thirdly,a method of visible analysis to enhance the accuracy of forest fire positioning is examined and realized;the method includes decreasing the visual angle,selecting central points,selecting the largest spots,and judging the selection of fire spots according to the central distance.Case studies are examined and the results are found to be satisfactory.展开更多
单一算法指纹自动识别系统在LT比对(即正查——现场比十指Latent to Ten-print)时均存在一定的漏比率(即错误拒绝率FRR),不同算法指纹自动识别系统错误拒绝的样本并不完全重合,即不同识别算法之间存在互补性。本文通过在一套指纹自动识...单一算法指纹自动识别系统在LT比对(即正查——现场比十指Latent to Ten-print)时均存在一定的漏比率(即错误拒绝率FRR),不同算法指纹自动识别系统错误拒绝的样本并不完全重合,即不同识别算法之间存在互补性。本文通过在一套指纹自动识别系统中同时加载多套不同来源算法进行比对,获得各套算法单独比对、融合比对的结果,再通过对这些比对结果的分析、比较,验证了不同识别算法具有互补性,使用多套异构识别算法进行比对,能够有效降低错误拒绝率,提高识别系统的比对精度这一结论。展开更多
基金supported by the National High-Tech Research and Development Program of China("863"project)(Grant No.2006AA06Z418)
文摘Forest fires are frequent natural disasters.It is necessary to explore advanced means to monitor,recognize and locate forest fires so as to establish a scientific system for the early detection,real-time positioning and quick fighting of forest fires.This paper mainly expounds methods and algorithms for improving accuracy and removing uncertainty in image-based forest fire recognition and spatial positioning.Firstly,we discuss a method of forest fire recognition in visible-light imagery.There are four aspects to improve accuracy and remove uncertainty in fire recognition:(1)eliminating factors of interference such as road and sky with high brightness,red leaves,other colored objects and objects that are lit up at night,(2)excluding imaging for specific periods and azimuth angles for which interference phenomena repeatedly occur,(3)improving the thresholding method for determining the flame border in image processing by adjusting the threshold to the season,weather and region,and (4)integrating the visible-light image method with infrared image technology.Secondly,we examine infrared-image-based methods and approaches of improving the accuracy of forest fire recognition by combining the spectrum threshold with an object feature value such as the normalized difference vegetation index and excluding factors of disturbance such as interference signals,extreme weather and high-temperature animals.Thirdly,a method of visible analysis to enhance the accuracy of forest fire positioning is examined and realized;the method includes decreasing the visual angle,selecting central points,selecting the largest spots,and judging the selection of fire spots according to the central distance.Case studies are examined and the results are found to be satisfactory.
文摘单一算法指纹自动识别系统在LT比对(即正查——现场比十指Latent to Ten-print)时均存在一定的漏比率(即错误拒绝率FRR),不同算法指纹自动识别系统错误拒绝的样本并不完全重合,即不同识别算法之间存在互补性。本文通过在一套指纹自动识别系统中同时加载多套不同来源算法进行比对,获得各套算法单独比对、融合比对的结果,再通过对这些比对结果的分析、比较,验证了不同识别算法具有互补性,使用多套异构识别算法进行比对,能够有效降低错误拒绝率,提高识别系统的比对精度这一结论。
