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Hyperspectral detection of citrus damage with Mahalanobis kernel classifier

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URI
http://hdl.handle.net/20.500.11939/5293
DOI
10.1049/el:20070906
Derechos de acceso
openAccess
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Author
Gómez-Sanchís, Juan; Blasco, José; Moltó, Enrique; Camps-Valls, G.
Date
2007
Cita bibliográfica
Gomez, J., Blasco, J., Moltó, E., Camps-Valls, G. (2007). Hyperspectral detection of citrus damage with Mahalanobis kernel classifier. Electronics Letters, 43(20), 1082-1084.
Abstract
Presented is a full computer vision system for the identification of post-harvest damage in citrus packing houses. The method is based on the combined use of hyperspectral images and the Mahalanobis kernel classifier. More accurate and reliable results compared to other methods are obtained in several scenarios and acquired images.
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