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Slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding

Slight crack of cottonseed is a critical factor influencing the germination rate of cotton due to foamed acid or water entering cottonseed through testa. However, it is very difficult to detect cottonseed with slight crack using common non-destructive detection methods, such as machine vision, optic...

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Autores principales: Zhang, Chi, Huang, Wenqian, Liang, Xiaoting, He, Xin, Tian, Xi, Chen, Liping, Wang, Qingyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9520625/
https://www.ncbi.nlm.nih.gov/pubmed/36186064
http://dx.doi.org/10.3389/fpls.2022.956636
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author Zhang, Chi
Huang, Wenqian
Liang, Xiaoting
He, Xin
Tian, Xi
Chen, Liping
Wang, Qingyan
author_facet Zhang, Chi
Huang, Wenqian
Liang, Xiaoting
He, Xin
Tian, Xi
Chen, Liping
Wang, Qingyan
author_sort Zhang, Chi
collection PubMed
description Slight crack of cottonseed is a critical factor influencing the germination rate of cotton due to foamed acid or water entering cottonseed through testa. However, it is very difficult to detect cottonseed with slight crack using common non-destructive detection methods, such as machine vision, optical spectroscopy, and thermal imaging, because slight crack has little effect on morphology, chemical substances or temperature. By contrast, the acoustic method shows a sensitivity to fine structure defects and demonstrates potential application in seed detection. This paper presents a novel method to detect slightly cracked cottonseed using air-coupled ultrasound with a light-weight vision transformer (ViT) and a sound-to-image encoding method. The echo signal of air-coupled ultrasound from cottonseed is obtained by non-contact and non-destructive methods. The intrinsic mode functions (IMFs) of ultrasound signal are obtained as the sound features using variational mode decomposition (VMD) approach. Then the sound features are converted into colorful images by a color encoding method. This method uses different colored lines to represent the changes of different values of IMFs according to the specified encoding period. A light-weight MobileViT method is utilized to identify the slightly cracked cottonseeds using encoding colorful images corresponding to cottonseeds. The experimental results show an average overall recognition accuracy of 90.7% for slightly cracked cottonseed from normal cottonseed, which indicates that the proposed method is reliable to applications in detection task of cottonseed with slight crack.
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spelling pubmed-95206252022-09-30 Slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding Zhang, Chi Huang, Wenqian Liang, Xiaoting He, Xin Tian, Xi Chen, Liping Wang, Qingyan Front Plant Sci Plant Science Slight crack of cottonseed is a critical factor influencing the germination rate of cotton due to foamed acid or water entering cottonseed through testa. However, it is very difficult to detect cottonseed with slight crack using common non-destructive detection methods, such as machine vision, optical spectroscopy, and thermal imaging, because slight crack has little effect on morphology, chemical substances or temperature. By contrast, the acoustic method shows a sensitivity to fine structure defects and demonstrates potential application in seed detection. This paper presents a novel method to detect slightly cracked cottonseed using air-coupled ultrasound with a light-weight vision transformer (ViT) and a sound-to-image encoding method. The echo signal of air-coupled ultrasound from cottonseed is obtained by non-contact and non-destructive methods. The intrinsic mode functions (IMFs) of ultrasound signal are obtained as the sound features using variational mode decomposition (VMD) approach. Then the sound features are converted into colorful images by a color encoding method. This method uses different colored lines to represent the changes of different values of IMFs according to the specified encoding period. A light-weight MobileViT method is utilized to identify the slightly cracked cottonseeds using encoding colorful images corresponding to cottonseeds. The experimental results show an average overall recognition accuracy of 90.7% for slightly cracked cottonseed from normal cottonseed, which indicates that the proposed method is reliable to applications in detection task of cottonseed with slight crack. Frontiers Media S.A. 2022-09-15 /pmc/articles/PMC9520625/ /pubmed/36186064 http://dx.doi.org/10.3389/fpls.2022.956636 Text en Copyright © 2022 Zhang, Huang, Liang, He, Tian, Chen and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Zhang, Chi
Huang, Wenqian
Liang, Xiaoting
He, Xin
Tian, Xi
Chen, Liping
Wang, Qingyan
Slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding
title Slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding
title_full Slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding
title_fullStr Slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding
title_full_unstemmed Slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding
title_short Slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding
title_sort slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9520625/
https://www.ncbi.nlm.nih.gov/pubmed/36186064
http://dx.doi.org/10.3389/fpls.2022.956636
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