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Image clustering technique in oil palm fresh fruit bunch (FFB) growth modeling

Digital images of FFB from anthesis to harvesting stage were acquired and grouped into 25 maturity stages. K-means clustering technique was used to separate the images into three colours clusters that represent three FFB features, Fruitlet, Brown spine and Green spine. The relationship of Hue colour...

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Main Authors: Mohd Kassim, Muhamad Saufi, Wan Ismail, Wan Ishak, Ramli, Abdul Rahman, Bejo, Siti Khairunniza
Format: Article
Language:English
Published: Elsevier 2014
Online Access:http://psasir.upm.edu.my/id/eprint/37930/1/37930.pdf
http://psasir.upm.edu.my/id/eprint/37930/
http://www.sciencedirect.com/science/article/pii/S2210784314000485
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spelling my.upm.eprints.379302015-12-29T11:02:52Z http://psasir.upm.edu.my/id/eprint/37930/ Image clustering technique in oil palm fresh fruit bunch (FFB) growth modeling Mohd Kassim, Muhamad Saufi Wan Ismail, Wan Ishak Ramli, Abdul Rahman Bejo, Siti Khairunniza Digital images of FFB from anthesis to harvesting stage were acquired and grouped into 25 maturity stages. K-means clustering technique was used to separate the images into three colours clusters that represent three FFB features, Fruitlet, Brown spine and Green spine. The relationship of Hue colour component and FFB maturity stages was established. The FFB was found to grow in three major stages, from week 0 to 5, week 6 to 14 and week 15 to 24. From the relationship a Growth Model was developed and was validated with actual maturity stage. The coefficient of determination, R2 was 0.95. Elsevier 2014 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/37930/1/37930.pdf Mohd Kassim, Muhamad Saufi and Wan Ismail, Wan Ishak and Ramli, Abdul Rahman and Bejo, Siti Khairunniza (2014) Image clustering technique in oil palm fresh fruit bunch (FFB) growth modeling. Agriculture and Agricultural Science Procedia, 2. pp. 337-344. ISSN 2210-7843 http://www.sciencedirect.com/science/article/pii/S2210784314000485 10.1016/j.aaspro.2014.11.047
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Digital images of FFB from anthesis to harvesting stage were acquired and grouped into 25 maturity stages. K-means clustering technique was used to separate the images into three colours clusters that represent three FFB features, Fruitlet, Brown spine and Green spine. The relationship of Hue colour component and FFB maturity stages was established. The FFB was found to grow in three major stages, from week 0 to 5, week 6 to 14 and week 15 to 24. From the relationship a Growth Model was developed and was validated with actual maturity stage. The coefficient of determination, R2 was 0.95.
format Article
author Mohd Kassim, Muhamad Saufi
Wan Ismail, Wan Ishak
Ramli, Abdul Rahman
Bejo, Siti Khairunniza
spellingShingle Mohd Kassim, Muhamad Saufi
Wan Ismail, Wan Ishak
Ramli, Abdul Rahman
Bejo, Siti Khairunniza
Image clustering technique in oil palm fresh fruit bunch (FFB) growth modeling
author_facet Mohd Kassim, Muhamad Saufi
Wan Ismail, Wan Ishak
Ramli, Abdul Rahman
Bejo, Siti Khairunniza
author_sort Mohd Kassim, Muhamad Saufi
title Image clustering technique in oil palm fresh fruit bunch (FFB) growth modeling
title_short Image clustering technique in oil palm fresh fruit bunch (FFB) growth modeling
title_full Image clustering technique in oil palm fresh fruit bunch (FFB) growth modeling
title_fullStr Image clustering technique in oil palm fresh fruit bunch (FFB) growth modeling
title_full_unstemmed Image clustering technique in oil palm fresh fruit bunch (FFB) growth modeling
title_sort image clustering technique in oil palm fresh fruit bunch (ffb) growth modeling
publisher Elsevier
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/37930/1/37930.pdf
http://psasir.upm.edu.my/id/eprint/37930/
http://www.sciencedirect.com/science/article/pii/S2210784314000485
_version_ 1643832101549637632
score 13.211869

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