Identifying the dominant species of tropical wood species using histogram intersection method

This research is addresses to determine the dominant species that located in the overlapped clusters produced by the Kohonen Self-organizing Map (KSOM). Before, KSOM algorithm able to cluster the tropical wood species data set effectively and accurately according to the wood features, which is wood...

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Published in:IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society
Main Author: Ahmad A.; Yusof R.; Mitsukura Y.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2015
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973098140&doi=10.1109%2fIECON.2015.7392572&partnerID=40&md5=1c483c0571014b03b34cb73e0d02daee
id 2-s2.0-84973098140
spelling 2-s2.0-84973098140
Ahmad A.; Yusof R.; Mitsukura Y.
Identifying the dominant species of tropical wood species using histogram intersection method
2015
IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society


10.1109/IECON.2015.7392572
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973098140&doi=10.1109%2fIECON.2015.7392572&partnerID=40&md5=1c483c0571014b03b34cb73e0d02daee
This research is addresses to determine the dominant species that located in the overlapped clusters produced by the Kohonen Self-organizing Map (KSOM). Before, KSOM algorithm able to cluster the tropical wood species data set effectively and accurately according to the wood features, which is wood pores sizes. Unfortunately, there are seven overlapped clusters in the clustering result and this is due to similarity features among the wood species. This problem has caused difficulty in determining the separation boundary amongst clusters, where the most dominant species for every overlapped cluster is difficult to identify. As for a solution, the Histogram Intersection (HI) method is proposed in this research to solve this problem. From the experiments, the HI has proved that it can determine the dominant species of the overlapped clusters effectively resulting in an improvement of 1.12% of the classification accuracy, compared with the clustering result without HI technique. It has shown the implementation of this method has successfully solved the problem occurred. © 2015 IEEE.
Institute of Electrical and Electronics Engineers Inc.

English
Conference paper

author Ahmad A.; Yusof R.; Mitsukura Y.
spellingShingle Ahmad A.; Yusof R.; Mitsukura Y.
Identifying the dominant species of tropical wood species using histogram intersection method
author_facet Ahmad A.; Yusof R.; Mitsukura Y.
author_sort Ahmad A.; Yusof R.; Mitsukura Y.
title Identifying the dominant species of tropical wood species using histogram intersection method
title_short Identifying the dominant species of tropical wood species using histogram intersection method
title_full Identifying the dominant species of tropical wood species using histogram intersection method
title_fullStr Identifying the dominant species of tropical wood species using histogram intersection method
title_full_unstemmed Identifying the dominant species of tropical wood species using histogram intersection method
title_sort Identifying the dominant species of tropical wood species using histogram intersection method
publishDate 2015
container_title IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society
container_volume
container_issue
doi_str_mv 10.1109/IECON.2015.7392572
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973098140&doi=10.1109%2fIECON.2015.7392572&partnerID=40&md5=1c483c0571014b03b34cb73e0d02daee
description This research is addresses to determine the dominant species that located in the overlapped clusters produced by the Kohonen Self-organizing Map (KSOM). Before, KSOM algorithm able to cluster the tropical wood species data set effectively and accurately according to the wood features, which is wood pores sizes. Unfortunately, there are seven overlapped clusters in the clustering result and this is due to similarity features among the wood species. This problem has caused difficulty in determining the separation boundary amongst clusters, where the most dominant species for every overlapped cluster is difficult to identify. As for a solution, the Histogram Intersection (HI) method is proposed in this research to solve this problem. From the experiments, the HI has proved that it can determine the dominant species of the overlapped clusters effectively resulting in an improvement of 1.12% of the classification accuracy, compared with the clustering result without HI technique. It has shown the implementation of this method has successfully solved the problem occurred. © 2015 IEEE.
publisher Institute of Electrical and Electronics Engineers Inc.
issn
language English
format Conference paper
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record_format scopus
collection Scopus
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