Cargando…

An Online Tea Fixation State Monitoring Algorithm Based on Image Energy Attention Mechanism and Supervised Clustering (IEAMSC)

This study aimed at the shortcomings of existing fixation algorithms that are image-based only, and an effective tea fixation state monitoring algorithm was proposed. An adaptive filtering algorithm was used to automatically filter the ineffective information. Using the energy extractor, the complet...

Descripción completa

Detalles Bibliográficos
Autores principales: Yu, Zhiyong, Wang, Jin, Zheng, Tao, Lu, Guodong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435818/
https://www.ncbi.nlm.nih.gov/pubmed/32748859
http://dx.doi.org/10.3390/s20154312
_version_ 1783572410797129728
author Yu, Zhiyong
Wang, Jin
Zheng, Tao
Lu, Guodong
author_facet Yu, Zhiyong
Wang, Jin
Zheng, Tao
Lu, Guodong
author_sort Yu, Zhiyong
collection PubMed
description This study aimed at the shortcomings of existing fixation algorithms that are image-based only, and an effective tea fixation state monitoring algorithm was proposed. An adaptive filtering algorithm was used to automatically filter the ineffective information. Using the energy extractor, the complete energy information of each fixation image was extracted. The image energy attention mechanism was used to identify the prominent features, and based on these, the energy data was mapped to generate the data points as the training data. The cluster idea was adopted, and the training data feed the features trainer. The trend center data of the tea processing energy clustering was generated from different color channels. The corresponding decision function was designed which is based on the distance of the cluster center. The fixation degree of each monitoring image set was measured by the decision function. The Euclidean distance of the energy clustering center of the three channels with the same fixation time progressively approached. The triangle formed by these three points had a trend of gradually shrinking, which was first discovered by us. The detection results showed high accuracy compared with the common classification algorithms. It indicates that the algorithm proposed has positive guiding and reference significance.
format Online
Article
Text
id pubmed-7435818
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-74358182020-08-25 An Online Tea Fixation State Monitoring Algorithm Based on Image Energy Attention Mechanism and Supervised Clustering (IEAMSC) Yu, Zhiyong Wang, Jin Zheng, Tao Lu, Guodong Sensors (Basel) Article This study aimed at the shortcomings of existing fixation algorithms that are image-based only, and an effective tea fixation state monitoring algorithm was proposed. An adaptive filtering algorithm was used to automatically filter the ineffective information. Using the energy extractor, the complete energy information of each fixation image was extracted. The image energy attention mechanism was used to identify the prominent features, and based on these, the energy data was mapped to generate the data points as the training data. The cluster idea was adopted, and the training data feed the features trainer. The trend center data of the tea processing energy clustering was generated from different color channels. The corresponding decision function was designed which is based on the distance of the cluster center. The fixation degree of each monitoring image set was measured by the decision function. The Euclidean distance of the energy clustering center of the three channels with the same fixation time progressively approached. The triangle formed by these three points had a trend of gradually shrinking, which was first discovered by us. The detection results showed high accuracy compared with the common classification algorithms. It indicates that the algorithm proposed has positive guiding and reference significance. MDPI 2020-08-02 /pmc/articles/PMC7435818/ /pubmed/32748859 http://dx.doi.org/10.3390/s20154312 Text en © 2020 by the authors. 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/).
spellingShingle Article
Yu, Zhiyong
Wang, Jin
Zheng, Tao
Lu, Guodong
An Online Tea Fixation State Monitoring Algorithm Based on Image Energy Attention Mechanism and Supervised Clustering (IEAMSC)
title An Online Tea Fixation State Monitoring Algorithm Based on Image Energy Attention Mechanism and Supervised Clustering (IEAMSC)
title_full An Online Tea Fixation State Monitoring Algorithm Based on Image Energy Attention Mechanism and Supervised Clustering (IEAMSC)
title_fullStr An Online Tea Fixation State Monitoring Algorithm Based on Image Energy Attention Mechanism and Supervised Clustering (IEAMSC)
title_full_unstemmed An Online Tea Fixation State Monitoring Algorithm Based on Image Energy Attention Mechanism and Supervised Clustering (IEAMSC)
title_short An Online Tea Fixation State Monitoring Algorithm Based on Image Energy Attention Mechanism and Supervised Clustering (IEAMSC)
title_sort online tea fixation state monitoring algorithm based on image energy attention mechanism and supervised clustering (ieamsc)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435818/
https://www.ncbi.nlm.nih.gov/pubmed/32748859
http://dx.doi.org/10.3390/s20154312
work_keys_str_mv AT yuzhiyong anonlineteafixationstatemonitoringalgorithmbasedonimageenergyattentionmechanismandsupervisedclusteringieamsc
AT wangjin anonlineteafixationstatemonitoringalgorithmbasedonimageenergyattentionmechanismandsupervisedclusteringieamsc
AT zhengtao anonlineteafixationstatemonitoringalgorithmbasedonimageenergyattentionmechanismandsupervisedclusteringieamsc
AT luguodong anonlineteafixationstatemonitoringalgorithmbasedonimageenergyattentionmechanismandsupervisedclusteringieamsc
AT yuzhiyong onlineteafixationstatemonitoringalgorithmbasedonimageenergyattentionmechanismandsupervisedclusteringieamsc
AT wangjin onlineteafixationstatemonitoringalgorithmbasedonimageenergyattentionmechanismandsupervisedclusteringieamsc
AT zhengtao onlineteafixationstatemonitoringalgorithmbasedonimageenergyattentionmechanismandsupervisedclusteringieamsc
AT luguodong onlineteafixationstatemonitoringalgorithmbasedonimageenergyattentionmechanismandsupervisedclusteringieamsc