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Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment

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Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment

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dc.contributor.author Lorente, D. es_ES
dc.contributor.author Aleixos Borrás, María Nuria es_ES
dc.contributor.author Gómez Sanchís, Juan es_ES
dc.contributor.author Cubero, S. es_ES
dc.contributor.author García Navarrete, Óscar Leonardo es_ES
dc.contributor.author Blasco Ivars, José es_ES
dc.date.accessioned 2016-07-22T11:25:06Z
dc.date.available 2016-07-22T11:25:06Z
dc.date.issued 2011-05
dc.identifier.issn 1935-5130
dc.identifier.uri http://hdl.handle.net/10251/68034
dc.description.abstract [EN] Hyperspectral imaging systems are starting to be used as a scientific tool for food quality assessment. A typical hyperspectral image is composed of a set of a relatively wide range of monochromatic images corresponding to continuous wavelengths that normally contain redundant information or may exhibit a high degree of correlation. In addition, computation of the classifiers used to deal with the data obtained from the images can become excessively complex and time-consuming for such high-dimensional datasets, and this makes it difficult to incorporate such systems into an industry that demands standard protocols or high-speed processes. Therefore, recent works have focused on the development of new systems based on this technology that are capable of analysing quality features that cannot be inspected using visible imaging. Many of those studies have also centred on finding new statistical techniques to reduce the hyperspectral images to multispectral ones, which are easier to implement in automatic, non-destructive systems. This article reviews recent works that use hyperspectral imaging for the inspection of fruit and vegetables. It explains the different technologies available to acquire the images and their use for the non-destructive inspection of the internal and external features of these products. Particular attention is paid to the works aimed at reducing the dimensionality of the images, with details of the statistical techniques most commonly used for this task. © 2011 Springer Science+Business Media, LLC. es_ES
dc.description.sponsorship This work was partially funded by the Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria de Espana (INIA) through research project RTA2009-00118-C02-01 and by the Ministerio de Ciencia e Innovacion de Espana (MICINN) through research project DPI2010-19457, both projects with the support of European FEDER funds. This work was also been partially funded by the Universitat de Valencia through project UV-INV-AE11-41271.
dc.language Inglés es_ES
dc.publisher Springer Verlag es_ES
dc.relation INIA/RTA2009-00118-C02-01 es_ES
dc.relation MICINN/DPI2010-19457 es_ES
dc.relation UV/UV-INV-AE11-41271 es_ES
dc.relation.ispartof Food and Bioprocess Technology es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Computer vision es_ES
dc.subject Fruits es_ES
dc.subject Hyperspectral imaging es_ES
dc.subject Image analysis es_ES
dc.subject Multispectral imaging es_ES
dc.subject Non-destructive inspection es_ES
dc.subject Quality es_ES
dc.subject Vegetables es_ES
dc.subject Data sets es_ES
dc.subject Degree of correlations es_ES
dc.subject External features es_ES
dc.subject Food quality es_ES
dc.subject Fruit and vegetables es_ES
dc.subject High-dimensional es_ES
dc.subject High-speed process es_ES
dc.subject Hyper-spectral images es_ES
dc.subject Hyperspectral imaging systems es_ES
dc.subject Monochromatic images es_ES
dc.subject Multi-spectral es_ES
dc.subject Non destructive es_ES
dc.subject Non destructive inspection es_ES
dc.subject Quality assessment es_ES
dc.subject Quality features es_ES
dc.subject Redundant informations es_ES
dc.subject Scientific tool es_ES
dc.subject Standard protocols es_ES
dc.subject Statistical techniques es_ES
dc.subject Visible imaging es_ES
dc.subject Image quality es_ES
dc.subject Independent component analysis es_ES
dc.subject.classification EXPRESION GRAFICA EN LA INGENIERIA es_ES
dc.title Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11947-011-0725-1
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Mecanización y Tecnología Agraria - Departament de Mecanització i Tecnologia Agrària es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Gráfica - Departament d'Enginyeria Gràfica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano - Institut Interuniversitari d'Investigació en Bioenginyeria i Tecnologia Orientada a l'Ésser Humà es_ES
dc.description.bibliographicCitation Lorente, D.; Aleixos Borrás, MN.; Gómez Sanchís, J.; Cubero, S.; García Navarrete, OL.; Blasco Ivars, J. (2011). Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment. Food and Bioprocess Technology. 5(4):1121-1142. doi:10.1007/s11947-011-0725-1 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/s11947-011-0725-1 es_ES
dc.description.upvformatpinicio 1121 es_ES
dc.description.upvformatpfin 1142 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 5 es_ES
dc.description.issue 4 es_ES
dc.relation.senia 212459 es_ES
dc.identifier.eissn 1935-5149
dc.contributor.funder Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA)
dc.contributor.funder Ministerio de Ciencia e Innovación (MICINN)
dc.contributor.funder Universitat de València (UV)
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