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Proceedings Paper

Development of algorithms for detection of mechanical injury on white mushrooms (Agaricus bisporus) using hyperspectral imaging
Author(s): A. A. Gowen; C. P. O'Donnell
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Paper Abstract

White mushrooms were subjected to mechanical injury by controlled shaking in a plastic box at 400 rpm for different times (0, 60, 120, 300 and 600 s). Immediately after shaking, hyperspectral images were obtained using two pushbroom line-scanning hyperspectral imaging instruments, one operating in the wavelength range of 400 - 1000 nm with spectroscopic resolution of 5 nm, the other operating in the wavelength range of 950 - 1700 nm with spectroscopic resolution of 7 nm. Different spectral and spatial pretreatments were investigated to reduce the effect of sample curvature on hyperspectral data. Algorithms based on Chemometric techniques (Principal Component Analysis and Partial Least Squares Discriminant Analysis) and image processing methods (masking, thresholding, morphological operations) were developed for pixel classification in hyperspectral images. In addition, correlation analysis, spectral angle mapping and scaled difference of sample spectra were investigated and compared with the chemometric approaches.

Paper Details

Date Published: 27 April 2009
PDF: 8 pages
Proc. SPIE 7315, Sensing for Agriculture and Food Quality and Safety, 73150G (27 April 2009); doi: 10.1117/12.818597
Show Author Affiliations
A. A. Gowen, Univ. College Dublin (Ireland)
C. P. O'Donnell, Univ. College Dublin (Ireland)


Published in SPIE Proceedings Vol. 7315:
Sensing for Agriculture and Food Quality and Safety
Moon S. Kim; Shu-I Tu; Kaunglin Chao, Editor(s)

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