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Chemometrics‐assisted color histogram‐based analytical systems
Author(s) -
Gonçalves Dias Diniz Paulo Henrique
Publication year - 2020
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.3242
Subject(s) - histogram , computer science , chemometrics , artificial intelligence , histogram equalization , pixel , computer vision , scanner , color histogram , histogram matching , pattern recognition (psychology) , image processing , color image , image (mathematics) , machine learning
Abstract This review systematizes for the first time the here called “Chemometrics‐assisted color histogram‐based analytical systems” under the acronym CACHAS. A comprehensive discussion of the fundamentals, general characteristics, and applications are presented in order to direct practical aspects for developing methods that use color histograms as input data for the construction of chemometric models. For this, analytical information is rapidly acquired using a simple image acquisition device (such as digital camera, webcam, scanner, or smartphone), without need for any image processing, other than extraction of the histograms, which are constructed by counting the frequency distribution of the different color tones (conveniently specified through a color space) of all pixels delimited by a region of interest in a digital image. As a consequence, CACHAS have been increasingly used for qualitative and quantitative purposes in food, agricultural, forensic, biomedical, and microbiological analysis, reinforcing the principles of green analytical chemistry.