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Descripción
In this paper, we propose a system for authenticating local bee pollen against fraudulent samples using image processing and classification techniques. Our system is based on the colour properties of bee pollen loads and the use of one-class classifiers to reject unknown pollen samples. The latter classification techniques allow us to tackle the major difficulty of the problem, the existence of many possible fraudulent pollen types. Also presented is a multi-classifier model with an ambiguity discovery process to fuse the output of the one-class classifiers. The method is validated by authenticating Spanish bee pollen types, the overall accuracy of the final system of being 94%. Therefore, the system is able to rapidly reject the non-local pollen samples with inexpensive hardware and without the need to send the product to the laboratory. ? 2012 Elsevier Ltd. All rights reserved.
Internacional	Si
JCR del ISI	Si
Título de la revista	Journal of Food Engineering
ISSN	0260-8774
Factor de impacto JCR	2,414
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Desde la página	50
Hasta la página	59
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• Autor: Pascual Campoy Cervera (UPM)

• Creador: Grupo de Investigación: Computer Vision
• Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
• Departamento: Automática, Ingeniería Electrónica e Informática Industrial