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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...

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Main Authors: Vitale, Raffaele, Prats-Montalbán, José M., López-García, Fernando, Blasco, José, Ferrer, Alberto
Format: article
Language:Inglés
Published: Wiley 2021
Subjects:
Color information
Graphs
Multivariate image analysis
Segmentation
Textural information
U30 Research methods
N01 Agricultural engineering
Online Access:http://hdl.handle.net/20.500.11939/6958
https://onlinelibrary.wiley.com/doi/full/10.1002/cem.2854
Summary: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.

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