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Electronic Eye Based on RGB Analysis for the Identification of Tequilas
The present work reports the development of a biologically inspired analytical system known as Electronic Eye (EE), capable of qualitatively discriminating different tequila categories. The reported system is a low-cost and portable instrumentation based on a Raspberry Pi single-board computer and a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8000478/ https://www.ncbi.nlm.nih.gov/pubmed/33801493 http://dx.doi.org/10.3390/bios11030068 |
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author | Gómez, Anais Bueno, Diana Gutiérrez, Juan Manuel |
author_facet | Gómez, Anais Bueno, Diana Gutiérrez, Juan Manuel |
author_sort | Gómez, Anais |
collection | PubMed |
description | The present work reports the development of a biologically inspired analytical system known as Electronic Eye (EE), capable of qualitatively discriminating different tequila categories. The reported system is a low-cost and portable instrumentation based on a Raspberry Pi single-board computer and an 8 Megapixel CMOS image sensor, which allow the collection of images of Silver, Aged, and Extra-aged tequila samples. Image processing is performed mimicking the trichromatic theory of color vision using an analysis of Red, Green, and Blue components (RGB) for each image’s pixel. Consequently, RGB absorbances of images were evaluated and preprocessed, employing Principal Component Analysis (PCA) to visualize data clustering. The resulting PCA scores were modeled with a Linear Discriminant Analysis (LDA) that accomplished the qualitative classification of tequilas. A Leave-One-Out Cross-Validation (LOOCV) procedure was performed to evaluate classifiers’ performance. The proposed system allowed the identification of real tequila samples achieving an overall classification rate of 90.02%, average sensitivity, and specificity of 0.90 and 0.96, respectively, while Cohen’s kappa coefficient was 0.87. In this case, the EE has demonstrated a favorable capability to correctly discriminated and classified the different tequila samples according to their categories. |
format | Online Article Text |
id | pubmed-8000478 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80004782021-03-28 Electronic Eye Based on RGB Analysis for the Identification of Tequilas Gómez, Anais Bueno, Diana Gutiérrez, Juan Manuel Biosensors (Basel) Article The present work reports the development of a biologically inspired analytical system known as Electronic Eye (EE), capable of qualitatively discriminating different tequila categories. The reported system is a low-cost and portable instrumentation based on a Raspberry Pi single-board computer and an 8 Megapixel CMOS image sensor, which allow the collection of images of Silver, Aged, and Extra-aged tequila samples. Image processing is performed mimicking the trichromatic theory of color vision using an analysis of Red, Green, and Blue components (RGB) for each image’s pixel. Consequently, RGB absorbances of images were evaluated and preprocessed, employing Principal Component Analysis (PCA) to visualize data clustering. The resulting PCA scores were modeled with a Linear Discriminant Analysis (LDA) that accomplished the qualitative classification of tequilas. A Leave-One-Out Cross-Validation (LOOCV) procedure was performed to evaluate classifiers’ performance. The proposed system allowed the identification of real tequila samples achieving an overall classification rate of 90.02%, average sensitivity, and specificity of 0.90 and 0.96, respectively, while Cohen’s kappa coefficient was 0.87. In this case, the EE has demonstrated a favorable capability to correctly discriminated and classified the different tequila samples according to their categories. MDPI 2021-03-02 /pmc/articles/PMC8000478/ /pubmed/33801493 http://dx.doi.org/10.3390/bios11030068 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article Gómez, Anais Bueno, Diana Gutiérrez, Juan Manuel Electronic Eye Based on RGB Analysis for the Identification of Tequilas |
title | Electronic Eye Based on RGB Analysis for the Identification of Tequilas |
title_full | Electronic Eye Based on RGB Analysis for the Identification of Tequilas |
title_fullStr | Electronic Eye Based on RGB Analysis for the Identification of Tequilas |
title_full_unstemmed | Electronic Eye Based on RGB Analysis for the Identification of Tequilas |
title_short | Electronic Eye Based on RGB Analysis for the Identification of Tequilas |
title_sort | electronic eye based on rgb analysis for the identification of tequilas |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8000478/ https://www.ncbi.nlm.nih.gov/pubmed/33801493 http://dx.doi.org/10.3390/bios11030068 |
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