DocumentCode :
3574019
Title :
NIR spectrometer used for material modeling with neural networks
Author :
Yee, Nigel
Author_Institution :
Electrotechnol. Dept., Unitec Inst. of Technol., Auckland, New Zealand
fYear :
2014
Firstpage :
1
Lastpage :
6
Abstract :
Near infrared multi-spectral image analysis is a tool used for non-destructive determination of biological material properties. In this investigation a custom built imaging spectrometer is constructed and used for the image spectra instrumentation and tests are performed on this instrument to determine its spectral resolution and spectral range; a biological data set (moisture in potato crisps) is then captured using this instrument and this data set is modeled using near infrared multi-spectral image analysis. A common problem with near infrared multi-spectral quantitative image measurements is light scatter and light non-linearity resulting from sample shape contours/curvatures and optical aberrations from optical component selection/layout. In this paper we detail an imaging spectrometer and the use of orthogonal signal correction preprocessing combined with a neural network full spectrum model for measurement of material property.
Keywords :
aberrations; computerised instrumentation; infrared imaging; infrared spectrometers; infrared spectroscopy; materials science computing; neural nets; nondestructive testing; NIR spectrometer; biological data set modeling; custom built imaging spectrometer; image spectra instrumentation; light nonlinearity; light scatter; material modeling; near infrared multispectral image analysis; near infrared multispectral quantitative image measurement; neural network full spectrum model; nondestructive biological material property determination; optical aberrations; optical component selection; orthogonal signal correction preprocessing; sample shape contour; sample shape curvature; spectral range determination; spectral resolution determination; Adaptive optics; Biological materials; Instruments; Moisture; Neural networks; Optical imaging; Neural network; biological material; near infrared spectrometer;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Engineering (APWC on CSE), 2014 Asia-Pacific World Congress on
Print_ISBN :
978-1-4799-1955-0
Type :
conf
DOI :
10.1109/APWCCSE.2014.7053878
Filename :
7053878
Link To Document :
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