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Lodged Sugarcane Assessment Using Digital Image Processing
Authors: Momin, Md Abdul, Wempe, Paul, Grift, Tony, Hansen, Alan
Identifier: CSBE17144
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Published in: CSBE-SCGAB Technical Conferences » AGM Winnipeg 2017 (with CIGR VI Technical Symposium)
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Description: Sugarcane lodging is a common issue, however, reliable methods of quantifying the degree of lodging have not been developed. The ability to assess the extent of lodging in the field using digital image processing techniques will lead to the implementation of many precision agriculture techniques, such as lodging maps to further the assessment of spatial variability within a cropping system. Images of lodged sugarcane in the field were acquired from various directions by installing camera at different locations of harvester, tractor and wagon. High resolution color camera was used to capture the lodged sugarcane images. These acquired sugarcane images were processed using various image processing techniques such as image segmentation, summing up binary pixels, texture analysis, edge detection, and vertical and horizontal edge pixel measurement to develop a robust image processing algorithm in order to detect and quantify lodging. Among different image processing approach presented in this study the vertical edge signature data showed works effectively. The relationship of vertical edge direction feature with degree of rotation for the upright green cane, lodged green and burnt sugarcane shown clear separation among them. The percent analysis in terms of pixel count of different type of sugarcane condition under various category of lodging were also observed. Upright green cane examples show much greater percentage of erect stems (on average 45%) and less amount of recumbent cane (on average 24%). Whereas for both condition of lodged cane the greater percentage of stem fall into recumbent category about on average 42%.
Keywords: Burnt sugarcane, unburnt sugarcane, lodging, erect, recumbent, edge detection
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Date: 2017-08-07
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Conference name: CSBE/SCGAB 2017 Annual Conference, Canad Inns Polo Park, Winnipeg, Manitoba, 6-10 August 2017.
Session name: Session 5C: Agricultural Machinery and Technologies
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Type: Text.Article
Format: PDF
Publication type: Technical conference
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Coverage: Canada
Language 1: en
Language 2:
Rights: Canadian Society for Bioengineering
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Other files:
DOI:
Description: Sugarcane lodging is a common issue, however, reliable methods of quantifying the degree of lodging have not been developed. The ability to assess the extent of lodging in the field using digital image processing techniques will lead to the implementation of many precision agriculture techniques, such as lodging maps to further the assessment of spatial variability within a cropping system. Images of lodged sugarcane in the field were acquired from various directions by installing camera at different locations of harvester, tractor and wagon. High resolution color camera was used to capture the lodged sugarcane images. These acquired sugarcane images were processed using various image processing techniques such as image segmentation, summing up binary pixels, texture analysis, edge detection, and vertical and horizontal edge pixel measurement to develop a robust image processing algorithm in order to detect and quantify lodging. Among different image processing approach presented in this study the vertical edge signature data showed works effectively. The relationship of vertical edge direction feature with degree of rotation for the upright green cane, lodged green and burnt sugarcane shown clear separation among them. The percent analysis in terms of pixel count of different type of sugarcane condition under various category of lodging were also observed. Upright green cane examples show much greater percentage of erect stems (on average 45%) and less amount of recumbent cane (on average 24%). Whereas for both condition of lodged cane the greater percentage of stem fall into recumbent category about on average 42%.
Keywords: Burnt sugarcane, unburnt sugarcane, lodging, erect, recumbent, edge detection
Résumé:
Mots-clés:
Citation:
Volume:
Issue:
Pages -
Contributor:
Date: 2017-08-07
Technical field:
Conference name: CSBE/SCGAB 2017 Annual Conference, Canad Inns Polo Park, Winnipeg, Manitoba, 6-10 August 2017.
Session name: Session 5C: Agricultural Machinery and Technologies
Other information:
Type: Text.Article
Format: PDF
Publication type: Technical conference
Source:
Relation:
Coverage: Canada
Language 1: en
Language 2:
Rights: Canadian Society for Bioengineering
Notes:
Other files:
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