Imaging Spectrograph and Camera Solutions for Industrial Applications

HERRALA, ESKO; Okkonen, Jukka

doi:10.1142/9789812797735_0005

Cited by 8 publications

(10 citation statements)

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“…Each band is an image, reflecting the intensity at a small part of the spectrum and at every pixel the intensity distribution over the associated spectrum can be studied. The spectral images in this experiment were obtained using ImSpector (Spectral Imaging Ltd, Oulu, Finland) spectrographs (Herrala and Mauri, 1993;Herrala and Okkonen, 1996;Hyvärinen et al, 1998) in combination with a stepper table. At each step the spectrum is recorded for one line of the object.…”

Section: Spectral Imagingmentioning

confidence: 99%

Detection of Fusarium in single wheat kernels using spectral imaging

Polder¹,

Heijden²,

Waalwijk³

et al. 2005

Seed Sci. Technol.

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Fusarium head blight (FHB) is a harmful fungal disease that occurs in small grains. Non-destructive detection of this disease is traditionally done using spectroscopy or image processing. In this paper the combination of these two in the form of spectral imaging is evaluated. Transmission spectral images are recorded, both in the visible and near-infrared range from FHB infected wheat kernels. These images are analyzed, using light absorption, the relation between two wavelength bands, unsupervised fuzzy c-means clustering and supervised partial least squares regression. The reference method for training and validation is TaqMan real-time PCR. Results show that nearinfrared spectral images perform much better than spectral images in the visible range. Kernels with more than 6000 pg Fusarium DNA could clearly be identified. Above 100 pg it was possible to predict the amount of Fusarium with a Q 2 of 0.8. This was both for Partial Least Squares regression (PLS) and a simple wavelength ratio. Also fuzzy c-means clustering shows a relation between amount of Fusarium and spectra.

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Section: Spectral Imagingmentioning

confidence: 99%

Detection of Fusarium in single wheat kernels using spectral imaging

Polder¹,

Heijden²,

Waalwijk³

et al. 2005

Seed Sci. Technol.

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“…In this experiment, we used the ImSpector (Spectral Imaging Ltd., Oulu, Finland) straight-axis imaging spectrograph, which uses a prism-grating-prism (PGP) dispersive element and transmission optics (Herrala and Okkonen, 1996;Hyvärinen et al, 1998).…”

Section: Imaging Spectrometrymentioning

confidence: 99%

Spectral Image Analysis for Measuring Ripeness of Tomatoes

Polder¹,

Heijden²,

Young³

2002

Transactions of the ASAE

146

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In this study, spectral images of five ripeness stages of tomatoes have been recorded and analyzed. The electromagnetic spectrum between 396 and 736 nm was recorded in 257 bands (every 1.3 nm). Results show that spectral images offer more discriminating power than standard RGB images for measuring ripeness stages of tomatoes. The classification error of individual pixels was reduced from 51% to 19%. Using a gray reference, the reflectance can be made invariant to the light source and even object geometry, which makes it possible to have comparable classification results over a large range of illumination conditions. Experimental results show that, although the error rate increases from 19% to 35% when using different light sources, it is still considerably below the 51% for RGB under a single light source.

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“…The push broom hyperspectral technique has been used for the last three decades [1,2] in industrial, airborne and satellite applications [3][4][5][6]. The push broom method records a perpendicular cross-section of any target along the track direction.…”

Section: Introductionmentioning

confidence: 99%

Do it yourself hyperspectral imager for handheld to airborne operations

Sigernes¹,

Syrjäsuo²,

Storvold³

et al. 2018

Opt. Express

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This study describes rapid prototype construction of small and lightweight push broom Hyper Spectral Imagers (HSI). The dispersive element housings are printed by a thermoplastic 3D printer combined with S-mount optical components and commercial off-the-shelf camera heads. Four models with a mass less than 200 g are presented with a spectral range in the visible to the near-infrared part of the electromagnetic spectrum. The bandpass is in the range from 1.4 - 5 nm. Three test experiments with motorized gimbals to stabilize attitude show that the instruments are capable of push broom spectral imaging from various platforms, including airborne drone to handheld operations.

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Imaging Spectrograph and Camera Solutions for Industrial Applications

Cited by 8 publications

References 0 publications

Detection of Fusarium in single wheat kernels using spectral imaging

Detection of Fusarium in single wheat kernels using spectral imaging

Spectral Image Analysis for Measuring Ripeness of Tomatoes

Do it yourself hyperspectral imager for handheld to airborne operations

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