Segmentation techniques in image analysis: A comparative study
Nowadays, the detection, localization, and quantification of different kinds of features in an RGB image (segmentation) is extremely helpful for, e.g., process monitoring or customer product acceptance. In this article, some of the most commonly used RGB image segmentation approaches are compared in...
| Main Authors: | , , , , |
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| Format: | article |
| Language: | Inglés |
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Wiley
2021
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11939/6958 https://onlinelibrary.wiley.com/doi/full/10.1002/cem.2854 |
| _version_ | 1855032521153052672 |
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| author | Vitale, Raffaele Prats-Montalbán, José M. López-García, Fernando Blasco, José Ferrer, Alberto |
| author_browse | Blasco, José Ferrer, Alberto López-García, Fernando Prats-Montalbán, José M. Vitale, Raffaele |
| author_facet | Vitale, Raffaele Prats-Montalbán, José M. López-García, Fernando Blasco, José Ferrer, Alberto |
| author_sort | Vitale, Raffaele |
| collection | ReDivia |
| description | Nowadays, the detection, localization, and quantification of different kinds of features in an RGB image (segmentation) is extremely helpful for, e.g., process monitoring or customer product acceptance. In this article, some of the most commonly used RGB image segmentation approaches are compared in an orange quality control case study. Analysis of variance and correspondence analysis are combined for determining their most relevant differences and highlighting their pros and cons. |
| format | article |
| id | ReDivia6958 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | ReDivia69582025-04-25T14:47:59Z Segmentation techniques in image analysis: A comparative study Vitale, Raffaele Prats-Montalbán, José M. López-García, Fernando Blasco, José Ferrer, Alberto Color information Graphs Multivariate image analysis Segmentation Textural information U30 Research methods N01 Agricultural engineering Nowadays, the detection, localization, and quantification of different kinds of features in an RGB image (segmentation) is extremely helpful for, e.g., process monitoring or customer product acceptance. In this article, some of the most commonly used RGB image segmentation approaches are compared in an orange quality control case study. Analysis of variance and correspondence analysis are combined for determining their most relevant differences and highlighting their pros and cons. 2021-01-12T08:11:37Z 2021-01-12T08:11:37Z 2016 article acceptedVersion Vitale, R., Prats‐Montalbán, J. M., López‐García, F., Blasco, J., & Ferrer, A. (2016). Segmentation techniques in image analysis: A comparative study. Journal of Chemometrics, 30(12), 749-758. 1099-128X http://hdl.handle.net/20.500.11939/6958 10.1002/cem.2854 https://onlinelibrary.wiley.com/doi/full/10.1002/cem.2854 en Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ openAccess Wiley electronico |
| spellingShingle | Color information Graphs Multivariate image analysis Segmentation Textural information U30 Research methods N01 Agricultural engineering Vitale, Raffaele Prats-Montalbán, José M. López-García, Fernando Blasco, José Ferrer, Alberto Segmentation techniques in image analysis: A comparative study |
| title | Segmentation techniques in image analysis: A comparative study |
| title_full | Segmentation techniques in image analysis: A comparative study |
| title_fullStr | Segmentation techniques in image analysis: A comparative study |
| title_full_unstemmed | Segmentation techniques in image analysis: A comparative study |
| title_short | Segmentation techniques in image analysis: A comparative study |
| title_sort | segmentation techniques in image analysis a comparative study |
| topic | Color information Graphs Multivariate image analysis Segmentation Textural information U30 Research methods N01 Agricultural engineering |
| url | http://hdl.handle.net/20.500.11939/6958 https://onlinelibrary.wiley.com/doi/full/10.1002/cem.2854 |
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