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A Novel Method of Identifying Paddy Seed Varieties
This paper presents a novel method for identifying three varieties (Taikong 9, Tainan 11, and Taikong 14) of foundation paddy seeds. Taikong 9, Tainan 11, and Taikong 14 paddy seeds are indistinguishable by inspectors during seed purity inspections. The proposed method uses image segmentation and a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422170/ https://www.ncbi.nlm.nih.gov/pubmed/28397773 http://dx.doi.org/10.3390/s17040809 |
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author | Huang, Kuo-Yi Chien, Mao-Chien |
author_facet | Huang, Kuo-Yi Chien, Mao-Chien |
author_sort | Huang, Kuo-Yi |
collection | PubMed |
description | This paper presents a novel method for identifying three varieties (Taikong 9, Tainan 11, and Taikong 14) of foundation paddy seeds. Taikong 9, Tainan 11, and Taikong 14 paddy seeds are indistinguishable by inspectors during seed purity inspections. The proposed method uses image segmentation and a key point identification algorithm that can segment paddy seed images and extract seed features. A back propagation neural network was used to establish a classifier based on seven features that could classify the three paddy seed varieties. The classification accuracies of the resultant classifier for varieties Taikong 9, Tainan 11, and Taikong 14 were 92.68%, 97.35% and 96.57%, respectively. The experimental results indicated that the three paddy seeds can be differentiated efficiently using the developed system. |
format | Online Article Text |
id | pubmed-5422170 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54221702017-05-12 A Novel Method of Identifying Paddy Seed Varieties Huang, Kuo-Yi Chien, Mao-Chien Sensors (Basel) Article This paper presents a novel method for identifying three varieties (Taikong 9, Tainan 11, and Taikong 14) of foundation paddy seeds. Taikong 9, Tainan 11, and Taikong 14 paddy seeds are indistinguishable by inspectors during seed purity inspections. The proposed method uses image segmentation and a key point identification algorithm that can segment paddy seed images and extract seed features. A back propagation neural network was used to establish a classifier based on seven features that could classify the three paddy seed varieties. The classification accuracies of the resultant classifier for varieties Taikong 9, Tainan 11, and Taikong 14 were 92.68%, 97.35% and 96.57%, respectively. The experimental results indicated that the three paddy seeds can be differentiated efficiently using the developed system. MDPI 2017-04-09 /pmc/articles/PMC5422170/ /pubmed/28397773 http://dx.doi.org/10.3390/s17040809 Text en © 2017 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 Huang, Kuo-Yi Chien, Mao-Chien A Novel Method of Identifying Paddy Seed Varieties |
title | A Novel Method of Identifying Paddy Seed Varieties |
title_full | A Novel Method of Identifying Paddy Seed Varieties |
title_fullStr | A Novel Method of Identifying Paddy Seed Varieties |
title_full_unstemmed | A Novel Method of Identifying Paddy Seed Varieties |
title_short | A Novel Method of Identifying Paddy Seed Varieties |
title_sort | novel method of identifying paddy seed varieties |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422170/ https://www.ncbi.nlm.nih.gov/pubmed/28397773 http://dx.doi.org/10.3390/s17040809 |
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