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Automatic measurement of numbers of maize seedlings based on mosaic imaging

The missing amount of planted corn seedlings plays an important role in corn yield, to acquire it automatically, a new system based on machine vision has been developed. System hardware includes: one Industrial Personal Computer, a Central Processing nit: Intel (r) CPU i5.4GHz, 4 Gb of memory, one m... Full description

Journal Title: Transactions of the Chinese Society of Agricultural Engineering/Nongye Gongcheng Xuebao June 2014, Vol.30(12), pp.148-153
Main Author: Wang, Chuanyu
Other Authors: Guo, Xinyu , Xiao, Boxiang , Du, Jianjun , Wu, Sheng
Format: Electronic Article Electronic Article
Language: chi
Subjects:
Quelle: © ProQuest LLC All rights reserved
ID: ISSN: 1002-6819 ; DOI: 10.3969/j.issn.1002-6819.2014.12.018
Link: http://search.proquest.com/docview/1770376640/?pq-origsite=primo
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title: Automatic measurement of numbers of maize seedlings based on mosaic imaging
format: Article
creator:
  • Wang, Chuanyu
  • Guo, Xinyu
  • Xiao, Boxiang
  • Du, Jianjun
  • Wu, Sheng
subjects:
  • Illumination
  • Corn
  • Lighting
  • High Density
  • Automation
  • Imaging
  • Manuals
  • Agricultural Engineering
  • Agricultural and Farm Machinery (Mt)
  • Land Development, Irrigation, and Drainage (CE)
  • Crops
  • Image Processing
  • Measurements
  • Image Sequences
  • Image Mosaic
  • Corn Seedling
  • Number of Seedlings Deficiency
ispartof: Transactions of the Chinese Society of Agricultural Engineering/Nongye Gongcheng Xuebao, June 2014, Vol.30(12), pp.148-153
description: The missing amount of planted corn seedlings plays an important role in corn yield, to acquire it automatically, a new system based on machine vision has been developed. System hardware includes: one Industrial Personal Computer, a Central Processing nit: Intel (r) CPU i5.4GHz, 4 Gb of memory, one mvc3000 high speed Industrial camera (24FPS), and one Pentax len 8.5 mm f/1.5. Firstly, image sequences obtained along plant rows from a top view under in-field lighting conditions were registered to the uniform coordinate system. In a high density experiment, measurement results of the method agree with a manual measurement 6 in 10 and 4 in 10 have a difference up to two plants. Comparison with a manual measurement and our method, a high correlation on the two methods was found; this method can replace manual measurement, reduce time cost and human labor effort, and improve the degree of automation of the corn seedling missing survey.
language: chi
source: © ProQuest LLC All rights reserved
identifier: ISSN: 1002-6819 ; DOI: 10.3969/j.issn.1002-6819.2014.12.018
fulltext: fulltext
issn:
  • 10026819
  • 1002-6819
url: Link


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titleAutomatic measurement of numbers of maize seedlings based on mosaic imaging
creatorWang, Chuanyu ; Guo, Xinyu ; Xiao, Boxiang ; Du, Jianjun ; Wu, Sheng
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ispartofTransactions of the Chinese Society of Agricultural Engineering/Nongye Gongcheng Xuebao, June 2014, Vol.30(12), pp.148-153
identifierISSN: 1002-6819 ; DOI: 10.3969/j.issn.1002-6819.2014.12.018
subjectIllumination ; Corn ; Lighting ; High Density ; Automation ; Imaging ; Manuals ; Agricultural Engineering ; Agricultural and Farm Machinery (Mt) ; Land Development, Irrigation, and Drainage (CE) ; Crops ; Image Processing ; Measurements ; Image Sequences ; Image Mosaic ; Corn Seedling ; Number of Seedlings Deficiency
descriptionThe missing amount of planted corn seedlings plays an important role in corn yield, to acquire it automatically, a new system based on machine vision has been developed. System hardware includes: one Industrial Personal Computer, a Central Processing nit: Intel (r) CPU i5.4GHz, 4 Gb of memory, one mvc3000 high speed Industrial camera (24FPS), and one Pentax len 8.5 mm f/1.5. Firstly, image sequences obtained along plant rows from a top view under in-field lighting conditions were registered to the uniform coordinate system. In a high density experiment, measurement results of the method agree with a manual measurement 6 in 10 and 4 in 10 have a difference up to two plants. Comparison with a manual measurement and our method, a high correlation on the two methods was found; this method can replace manual measurement, reduce time cost and human labor effort, and improve the degree of automation of the corn seedling missing survey.
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abstractThe missing amount of planted corn seedlings plays an important role in corn yield, to acquire it automatically, a new system based on machine vision has been developed. System hardware includes: one Industrial Personal Computer, a Central Processing nit: Intel (r) CPU i5.4GHz, 4 Gb of memory, one mvc3000 high speed Industrial camera (24FPS), and one Pentax len 8.5 mm f/1.5. Firstly, image sequences obtained along plant rows from a top view under in-field lighting conditions were registered to the uniform coordinate system. In a high density experiment, measurement results of the method agree with a manual measurement 6 in 10 and 4 in 10 have a difference up to two plants. Comparison with a manual measurement and our method, a high correlation on the two methods was found; this method can replace manual measurement, reduce time cost and human labor effort, and improve the degree of automation of the corn seedling missing survey.
doi10.3969/j.issn.1002-6819.2014.12.018
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date2014-06-01