首页> 外文会议>Next-Generation Spectroscopic Technologies IX >Built-in hyperspectral camera for smartphone in visible, near-infrared and middle-infrared lights region (third report): Spectroscopic imaging for broad-area and real-time componential analysis system against local unexpected terrorism and disasters
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Built-in hyperspectral camera for smartphone in visible, near-infrared and middle-infrared lights region (third report): Spectroscopic imaging for broad-area and real-time componential analysis system against local unexpected terrorism and disasters

机译:适用于智能手机的可见光,近红外光和中红外光区域的内置高光谱摄像头(第三次报告):针对大范围的光谱成像和实时成分分析系统,可应对本地意外的恐怖主义和灾难

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The distributed networks for information collection of chemical components with high-mobility objects, such as drones or smartphones, will work effectively for investigations, clarifications and predictions against unexpected local terrorisms and disasters like localized torrential downpours. We proposed and reported the proposed spectroscopic line-imager for smartphones in this conference. In this paper, we will mention the wide-area spectroscopic-image construction by estimating 6 DOF (Degrees Of Freedom: parallel movements=x,y,z and rotational movements=θ_x, θ_y, θ_Z) from line data to observe and analyze surrounding chemical-environments. Recently, smartphone movies, what were photographed by peoples happened to be there, had worked effectively to analyze what kinds of phenomenon had happened around there. But when a gas tank suddenly blew up, we did not recognize from visible-light RGB-color cameras what kinds of chemical gas components were polluting surrounding atmospheres. Conventionally Fourier spectroscopy had been well known as chemical components analysis in laboratory usages. But volatile gases should be analyzed promptly at accident sites. And because the humidity absorption in near and middle infrared lights has very high sensitivity, we will be able to detect humidity in the sky from wide field spectroscopic image. And also recently, 6-DOF sensors are easily utilized for estimation of position and attitude for UAV (Unmanned Air Vehicle) or smartphone. But for observing long-distance views, accuracies of angle measurements were not sufficient to merge line data because of leverage theory. Thus, by searching corresponding pixels between line spectroscopic images, we are trying to estimate 6-DOF in high accuracy.
机译:分布式网络用于收集具有高流动性物体(例如,无人机或智能手机)的化学成分的信息,可以有效地进行调查,澄清和预测,以应对意外的本地恐怖主义和局部倾盆大雨等灾害。我们在本次会议上提出并报告了建议的智能手机光谱线成像仪。在本文中,我们将通过从线数据中估算6个自由度(自由度:平行运动= x,y,z和旋转运动=θ_x,θ_y,θ_Z)来提及广域光谱图像的构造,以观察和分析周围的环境化学环境。最近,人们拍摄的智能手机电影恰好在那里,已经有效地分析了周围发生了什么现象。但是,当一个储气罐突然炸毁时,我们无法从可见光RGB彩色相机中识别出哪种化学气体成分正在污染周围的大气。常规上,傅立叶光谱在实验室用途中已被称为化学成分分析。但是,应该在事故现场及时分析挥发性气体。而且由于近红外和中红外光的吸湿具有很高的灵敏度,因此我们将能够从宽视场光谱图像中检测天空中的湿度。而且最近,6-DOF传感器也很容易用于评估UAV(无人机)或智能手机的位置和姿态。但是对于观察长距离视图,由于杠杆原理,角度测量的准确性不足以合并线数据。因此,通过搜索线光谱图像之间的对应像素,我们试图以高精度估计6自由度。

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