Feature extraction from oil palm in vitro shoot images
The feature extraction techniques are discussed in this article. The algorithms and methods developed are robust and advanced enough to be used in combination with a machine vision algorithm and automation system. The subject under study is oil palm in vitro shoot images. The potential features extr...
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Malaysian Palm Oil Board
2010
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my.upm.eprints.147402015-09-28T01:46:17Z http://psasir.upm.edu.my/id/eprint/14740/ Feature extraction from oil palm in vitro shoot images Ismail, Abdul Halim Marhaban, Mohammad Hamiruce Mohd Noor, Samsul Bahari Hashim, Ahmad Tarmizi The feature extraction techniques are discussed in this article. The algorithms and methods developed are robust and advanced enough to be used in combination with a machine vision algorithm and automation system. The subject under study is oil palm in vitro shoot images. The potential features extracted from the images could be used as a vision sensor to replace human expertise via an automation system. Two main categories of the in vitro shoots could be visually identified, namely the normal and abnormal groups. Image interpretation can categorize the in vitro shoot automatically in its group. The techniques proposed are not influenced by the shape or orientation of the in vitro shoot. The feature vector is plotted to prove the separability of both normal and abnormal in vitro shoots. Malaysian Palm Oil Board 2010-08 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/14740/1/Feature%20extraction%20from%20oil%20palm%20in%20vitro%20shoot%20images.pdf Ismail, Abdul Halim and Marhaban, Mohammad Hamiruce and Mohd Noor, Samsul Bahari and Hashim, Ahmad Tarmizi (2010) Feature extraction from oil palm in vitro shoot images. Journal of Oil Palm Research, 22 (2). pp. 765-773. ISSN 1511-2780 |
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The feature extraction techniques are discussed in this article. The algorithms and methods developed are robust and advanced enough to be used in combination with a machine vision algorithm and automation system. The subject under study is oil palm in vitro shoot images. The potential features extracted from the images could be used as a vision sensor to replace human expertise via an automation system. Two main categories of the in vitro shoots could be visually identified, namely the normal and abnormal groups. Image interpretation can categorize the in vitro shoot automatically in its group. The techniques proposed are not influenced by the shape or orientation of the in vitro shoot. The feature vector is plotted to prove the separability of both normal and abnormal in vitro shoots. |
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Article |
author |
Ismail, Abdul Halim Marhaban, Mohammad Hamiruce Mohd Noor, Samsul Bahari Hashim, Ahmad Tarmizi |
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Ismail, Abdul Halim Marhaban, Mohammad Hamiruce Mohd Noor, Samsul Bahari Hashim, Ahmad Tarmizi Feature extraction from oil palm in vitro shoot images |
author_facet |
Ismail, Abdul Halim Marhaban, Mohammad Hamiruce Mohd Noor, Samsul Bahari Hashim, Ahmad Tarmizi |
author_sort |
Ismail, Abdul Halim |
title |
Feature extraction from oil palm in vitro shoot images |
title_short |
Feature extraction from oil palm in vitro shoot images |
title_full |
Feature extraction from oil palm in vitro shoot images |
title_fullStr |
Feature extraction from oil palm in vitro shoot images |
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Feature extraction from oil palm in vitro shoot images |
title_sort |
feature extraction from oil palm in vitro shoot images |
publisher |
Malaysian Palm Oil Board |
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2010 |
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http://psasir.upm.edu.my/id/eprint/14740/1/Feature%20extraction%20from%20oil%20palm%20in%20vitro%20shoot%20images.pdf http://psasir.upm.edu.my/id/eprint/14740/ |
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