Machine vision for non destructive evaluation of fruit quality
The aim of this paper is to show preliminary results in developing image analysis techniques to measure some parameters that define the quality of different fruits and vegetables: size, colour, external defects and stem location. Because of the high efficiency of the segmentation procedure, estimati...
| Autores principales: | , , , , |
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| Otros Autores: | |
| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2017
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| Acceso en línea: | http://hdl.handle.net/20.500.11939/5660 |
| _version_ | 1855491961856720896 |
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| author | Moltó, Enrique Ruiz, L. A. Aleixos, Nuria Vazquez, J. Juste, Florentino |
| author2 | VanMeurs, WTM Gieling, TH Bennedsen, BS |
| author_browse | Aleixos, Nuria Juste, Florentino Moltó, Enrique Ruiz, L. A. VanMeurs, WTM Gieling, TH Bennedsen, BS Vazquez, J. |
| author_facet | VanMeurs, WTM Gieling, TH Bennedsen, BS Moltó, Enrique Ruiz, L. A. Aleixos, Nuria Vazquez, J. Juste, Florentino |
| author_sort | Moltó, Enrique |
| collection | ReDivia |
| description | The aim of this paper is to show preliminary results in developing image analysis techniques to measure some parameters that define the quality of different fruits and vegetables: size, colour, external defects and stem location. Because of the high efficiency of the segmentation procedure, estimation of size is solved for the fruit varieties in which experiments were performed. The partial coloured areas that appear on some varieties of peaches are also properly located. Greenish to red colour co-ordinates estimated from the vision system in tomatoes are well correlated with respect to standard colorimeter values. Damaged area is properly detected in oranges. Exact location of the stem is achieved in oranges and peaches. |
| format | Objeto de conferencia |
| id | ReDivia5660 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| record_format | dspace |
| spelling | ReDivia56602025-04-25T14:53:45Z Machine vision for non destructive evaluation of fruit quality ACTA HORTICULTURAE Moltó, Enrique Ruiz, L. A. Aleixos, Nuria Vazquez, J. Juste, Florentino VanMeurs, WTM Gieling, TH Bennedsen, BS The aim of this paper is to show preliminary results in developing image analysis techniques to measure some parameters that define the quality of different fruits and vegetables: size, colour, external defects and stem location. Because of the high efficiency of the segmentation procedure, estimation of size is solved for the fruit varieties in which experiments were performed. The partial coloured areas that appear on some varieties of peaches are also properly located. Greenish to red colour co-ordinates estimated from the vision system in tomatoes are well correlated with respect to standard colorimeter values. Damaged area is properly detected in oranges. Exact location of the stem is achieved in oranges and peaches. 2017-06-01T10:12:46Z 2017-06-01T10:12:46Z 1998 1998 conferenceObject Moltó, E., Ruiz, L.A., Aleixos, N., Vázquez, J. and Juste, F. (1998). Machine vision for non destructive evaluation of fruit quality. Acta Hortic. 421, 85-90 0567-7572; 90-6605-800-5 http://hdl.handle.net/20.500.11939/5660 10.17660/ActaHortic.1998.421.7 en openAccess Impreso |
| spellingShingle | Moltó, Enrique Ruiz, L. A. Aleixos, Nuria Vazquez, J. Juste, Florentino Machine vision for non destructive evaluation of fruit quality |
| title | Machine vision for non destructive evaluation of fruit quality |
| title_full | Machine vision for non destructive evaluation of fruit quality |
| title_fullStr | Machine vision for non destructive evaluation of fruit quality |
| title_full_unstemmed | Machine vision for non destructive evaluation of fruit quality |
| title_short | Machine vision for non destructive evaluation of fruit quality |
| title_sort | machine vision for non destructive evaluation of fruit quality |
| url | http://hdl.handle.net/20.500.11939/5660 |
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