Abstract
Hyperspectral line scan 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. Thus, it is only necessary to illuminate a narrow line shaped area across the sample. This is usually done with halogen spots which deliver an elliptical illumination spot at the sample. By using several spots in a row and superimposing the illumination spots the area of interest is covered. However, this leads to a non-homogeneous intensity distribution along the scan line and an illumination of a much larger area than necessary. In our approach we use readily available automotive H7 halogen headlight bulbs in combination with an elliptical reflector. We compare different approaches based on mirrors as well as lens arrays to compress the elliptical illumination spot into a line shaped illumination. We compare the different approaches by their intensity distribution of the light along the scanline and the footprint of the light source. Optical simulations and practical measurements of the different light sources are presented.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Regulation No 37 of the Economic Commission for Europe of the United Nations (UN/ECE) — Uniform provisions concerning the approval of filament lamps for use in approved lamp units of power-driven vehicles and of their trailers, Official Journal of the European Union (2014)
Arnold, T., De Biasio, M., Kammari, R., Sayar-Chand K.: Development of VIS/NIR hyperspectral imaging system for industrial sorting applications. In: Proc. Vol. 11727, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII; 117271B (2021) https://doi.org/10.1117/12.2587981, SPIE Defense + Commercial Sensing (2021)
Li, Q., He, X., Wang, Y., Liu, H., Xu, D., Guo, F.: Review of spectral imaging technology in biomedical engineering: achievements and challenges. J. Biomed. Opt. 18(10), 100901 (2013). https://doi.org/10.1117/1.JBO.18.10.100901
Groinig, M., Burgstaller, M., Pail, M.: Industrial application of a new camera system based on hyperspectral imaging for inline quality control of potatoes. Proc. OAGM (2011)
Bearman, G.H., Nelson, M.P., Cabib, D.: Spectral imaging: Instrumentation, applications, and analysis. In: Proc. SPIE International Society for Optical Engineering (2000)
Leitner, R., De Biasio, M., Arnold, T.: High-sensitivity hyperspectral imager for biomedical video diagnostic applications. In: Proc. SPIE: Smart Biomedical and Physiological Sensor Technologies VII (04 2010)
De Biasio, T.M., Arnold, R.L.: UAV based multi-spectral imaging system for environmental monitoring. Tech. Mess. 78(11), 503–507 (2011). https://doi.org/10.1524/teme.2011.0204
Amigo, J.M.: (ed.) “Hyperspectral imaging”. Elsevier Ltd. book series. Data handling in science and technology, vol. 32, pp/ 0–630 (2019)
Acknowledgement
This work was performed within the COMET Centre ASSIC Austrian Smart Systems Integration Research Center, which is funded by BMK, BMDW, and the Austrian provinces of Carinthia and Styria, within the framework of COMET - Competence Centres for Excellent Technologies. The COMET programme is run by FFG.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Arnold, T., Bereczki, T., Balthasar, D. (2023). Development of a New Line Illumination for Industrial Hyperspectral Imaging Systems. In: Suryadevara, N.K., George, B., Jayasundera, K.P., Mukhopadhyay, S.C. (eds) Sensing Technology. ICST 2022. Lecture Notes in Electrical Engineering, vol 1035. Springer, Cham. https://doi.org/10.1007/978-3-031-29871-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-031-29871-4_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-29870-7
Online ISBN: 978-3-031-29871-4
eBook Packages: EngineeringEngineering (R0)