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Segmentation techniques in image analysis: A comparative study
Author(s) -
Vitale Raffaele,
PratsMontalbán José Manuel,
LópezGarcía Fernando,
Blasco José,
Ferrer Alberto
Publication year - 2016
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2854
Subject(s) - artificial intelligence , computer science , segmentation , rgb color model , image segmentation , computer vision , pattern recognition (psychology)
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.