Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment
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 exh...
| Main Authors: | , , , , , |
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| Format: | Artículo |
| Language: | Inglés |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/20.500.11939/5536 |
| _version_ | 1855491941880299520 |
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| author | Lorente, Delia Aleixos, Nuria Gómez-Sanchís, Juan Cubero, Sergio García-Navarrete, Óscar L. Blasco, José |
| author_browse | Aleixos, Nuria Blasco, José Cubero, Sergio García-Navarrete, Óscar L. Gómez-Sanchís, Juan Lorente, Delia |
| author_facet | Lorente, Delia Aleixos, Nuria Gómez-Sanchís, Juan Cubero, Sergio García-Navarrete, Óscar L. Blasco, José |
| author_sort | Lorente, Delia |
| collection | ReDivia |
| description | 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. |
| format | Artículo |
| id | ReDivia5536 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| record_format | dspace |
| spelling | ReDivia55362025-04-25T14:43:14Z Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment Lorente, Delia Aleixos, Nuria Gómez-Sanchís, Juan Cubero, Sergio García-Navarrete, Óscar L. Blasco, José 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. 2017-06-01T10:12:31Z 2017-06-01T10:12:31Z 2012 MAY 2012 article acceptedVersion Lorente, D., Aleixos, N., Gomez-Sanchis, J., Cubero, S., Garcia-Navarrete, O. L., Blasco, J. (2012). Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment. Food and Bioprocess Technology, 5(4), 1121-1142. 1935-5130; 1935-5149 http://hdl.handle.net/20.500.11939/5536 10.1007/s11947-011-0725-1 en openAccess Impreso |
| spellingShingle | Lorente, Delia Aleixos, Nuria Gómez-Sanchís, Juan Cubero, Sergio García-Navarrete, Óscar L. Blasco, José Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment |
| title | Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment |
| title_full | Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment |
| title_fullStr | Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment |
| title_full_unstemmed | Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment |
| title_short | Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment |
| title_sort | recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment |
| url | http://hdl.handle.net/20.500.11939/5536 |
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