高光谱成像
分类
计算机科学
光学成像
遥感
全光谱成像
人工智能
计算机视觉
地质学
光学
物理
算法
作者
Thomas Arnold,Martin De Biasio,Raghavendra Kammari,Krithika Sayar-Chand
摘要
Hyperspectral imaging systems are used in industrial sorting solutions to differentiate materials by subtle spectral features (spectral fingerprint) which are not resolvable by the human eye. Prominent applications are the detection of contaminants in food or the separation of different types of plastic. Hyperspectral line scan systems are suitable for many high throughput applications. A line across the sample, perpendicular to the direction of the relative movement, is projected into an imaging spectrograph. The spectral information for each pixel along this line is projected along the second axis of the two-dimensional detector chip. By spatial scanning of the sample the spectral data cube gets recorded. This paper presents the development of a laboratory hyperspectral imaging system capable of acquiring spectral data in the range from 400nm to 1700 nm. Therefore, Specim hyperspectral cameras FX10 and FX17 are used. The laboratory setup mimics an industrial sorting machine and will be used for application development. State of the art machine learning algorithms are used for data classification. Selected sorting applications are presented.
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