首页> 外文会议>Conference on 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:可见光,近红外线和中红外灯区(第三次报告)的智能手机内置高光谱相机:广泛和实时成分分析系统的光谱成像,对当地意外恐怖主义和灾害

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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:具有高迁移率物体的化学成分的信息收集的分布式网络,例如无人机或智能手机,将有效地工作,以便对意外的当地恐怖主义和灾害等局部暴雨等灾害进行调查,澄清和预测。我们提出并报告了本次会议中智能手机的拟议光谱线成像仪。在本文中,我们将通过估计6 DOF(自由度:并行运动= x,y,z和x,y,z和旋转运动=θ_x,θ_y,θ_z)来提及广域光谱 - 图像构造从线数据以观察和分析周围化学环境。最近,智能手机电影,人们拍摄的是恰到好处的,有效地努力分析那里发生了什么样的现象。但是,当一个油箱突然吹起时,我们无法从可见光RGB彩色相机中识别出什么样的化学气体成分污染围绕大气压。传统上傅里叶光谱是在实验室用途中被称为化学成分分析的。但应在意外网站上迅速分析挥发性气体。由于近乎和中红外灯中的湿度吸收具有很高的灵敏度,因此我们将能够从宽场光谱图像中检测天空中的湿度。此外,最近,6-DOF传感器很容易用于估计UAV(无人驾驶飞行器)或智能手机的位置和态度。但对于观察长距离视图,由于杠杆理论,角度测量的精度不足以合并线路数据。因此,通过在线光谱图像之间搜索相应的像素,我们试图以高精度估计6-DOF。

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