Colour segmentation of citrus fruits images for stem location
After mechanical harvesting, Cirrus fruits with long stems may cause damage on adjacent fruits during transportation and storage. A first step to solve before measuring the stem and taking the decision of cutting it or not, is the orientation of fruits. For this purpose, an image analysis method to...
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| Formato: | conferenceObject |
| Lenguaje: | Inglés |
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Asociación Española de Reconocimiento de Formas y Análisis de Imágenes
2022
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| Acceso en línea: | http://hdl.handle.net/20.500.11939/7950 |
| _version_ | 1855032701794385920 |
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| author | Ruiz, L. A. Moltó, Enrique Juste, Florentino |
| author2 | Calvo, A. |
| author_browse | Calvo, A. Juste, Florentino Moltó, Enrique Ruiz, L. A. |
| author_facet | Calvo, A. Ruiz, L. A. Moltó, Enrique Juste, Florentino |
| author_sort | Ruiz, L. A. |
| collection | ReDivia |
| description | After mechanical harvesting, Cirrus fruits with long stems may cause damage on adjacent fruits during transportation and storage. A first step to solve before measuring the stem and taking the decision of cutting it or not, is the orientation of fruits. For this purpose, an image analysis method to locate the stem insertion point based on colour segmentation is proposed and evaluated.
Four classes were defined for segmentation: background, peel, stem-calyx and cut stem, and a classifier based on bayesian decision rules was developed assuming that the independent variables (RGB) followed a normal distribution function, and that the classes had equal covariance matrix. The results point out an excellent performance of the classifier for the first two classes, and
satisfactory for the other two. The location algorithm used information of areas and centroids to estimate the coordinates of the stem insertion point. From a total of 86 images tested, it was correctly estimated a 90,3% of times. The method resulted to be efficient for fruits without leaves appended to the stem. |
| format | conferenceObject |
| id | ReDivia7950 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Asociación Española de Reconocimiento de Formas y Análisis de Imágenes |
| publisherStr | Asociación Española de Reconocimiento de Formas y Análisis de Imágenes |
| record_format | dspace |
| spelling | ReDivia79502025-04-25T14:53:11Z Colour segmentation of citrus fruits images for stem location Ruiz, L. A. Moltó, Enrique Juste, Florentino Calvo, A. J10 Handling, transport, storage and protection of agricultural products N20 Agricultural machinery and equipment U30 Research methods Computer vision Automation Harvesting Colour Stems Orientation Citrus fruits After mechanical harvesting, Cirrus fruits with long stems may cause damage on adjacent fruits during transportation and storage. A first step to solve before measuring the stem and taking the decision of cutting it or not, is the orientation of fruits. For this purpose, an image analysis method to locate the stem insertion point based on colour segmentation is proposed and evaluated. Four classes were defined for segmentation: background, peel, stem-calyx and cut stem, and a classifier based on bayesian decision rules was developed assuming that the independent variables (RGB) followed a normal distribution function, and that the classes had equal covariance matrix. The results point out an excellent performance of the classifier for the first two classes, and satisfactory for the other two. The location algorithm used information of areas and centroids to estimate the coordinates of the stem insertion point. From a total of 86 images tested, it was correctly estimated a 90,3% of times. The method resulted to be efficient for fruits without leaves appended to the stem. 2022-03-04T16:41:36Z 2022-03-04T16:41:36Z 1995 conferenceObject Ruiz, L. A., Molto, E. & Juste, F. (1995). Colour segmentation of citrus fruits images for stem location. Preprints of the VI Spanish Symposium on Pattern Recognition and Image Analysis, 130-137. 84-605-2447-7 CO-444-1995 (Depósito Legal) http://hdl.handle.net/20.500.11939/7950 en 1995-04-03 VI Spanish Symposium on Pattern Recognition and Image Analysis Cordoba (Spain) Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ openAccess Asociación Española de Reconocimiento de Formas y Análisis de Imágenes electronico |
| spellingShingle | J10 Handling, transport, storage and protection of agricultural products N20 Agricultural machinery and equipment U30 Research methods Computer vision Automation Harvesting Colour Stems Orientation Citrus fruits Ruiz, L. A. Moltó, Enrique Juste, Florentino Colour segmentation of citrus fruits images for stem location |
| title | Colour segmentation of citrus fruits images for stem location |
| title_full | Colour segmentation of citrus fruits images for stem location |
| title_fullStr | Colour segmentation of citrus fruits images for stem location |
| title_full_unstemmed | Colour segmentation of citrus fruits images for stem location |
| title_short | Colour segmentation of citrus fruits images for stem location |
| title_sort | colour segmentation of citrus fruits images for stem location |
| topic | J10 Handling, transport, storage and protection of agricultural products N20 Agricultural machinery and equipment U30 Research methods Computer vision Automation Harvesting Colour Stems Orientation Citrus fruits |
| url | http://hdl.handle.net/20.500.11939/7950 |
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