Title :
Hyperspectral imaging for mushroom (agaricus bisporus) quality monitoring
Author :
Gowen, A.A. ; O´Donnell, C.P. ; Frias, J.M. ; Downey, G.
Author_Institution :
Sch. of Agric., Univ. Coll. Dublin, Dublin, Ireland
Abstract :
A method for mushroom quality grading based on hyperspectral image analysis in the wavelength range 400-1000 nm is presented. 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.
Keywords :
agriculture; image classification; least squares approximations; monitoring; principal component analysis; chemometric techniques; hyperspectral imaging; image processing; mushroom; partial least squares discriminant analysis; pixel classification; principal component analysis; quality monitoring; Calibration; Food technology; Hyperspectral imaging; Image analysis; Least squares methods; Monitoring; Pixel; Principal component analysis; Reflectivity; Testing; chemometrics; hyperspectral; imaging; mushrooms;
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009. WHISPERS '09. First Workshop on
Conference_Location :
Grenoble
Print_ISBN :
978-1-4244-4686-5
Electronic_ISBN :
978-1-4244-4687-2
DOI :
10.1109/WHISPERS.2009.5289074
