Proceedings of the 2nd International Conference on Advances in Computer Science and Engineering (CSE 2013)

Clustering the Tropical Wood Species Using Kohonen Self-Organizing Map (KSOM)

Authors
Ahmad Azlin, Yusof Rubiyah
Corresponding Author
Ahmad Azlin
Available Online July 2013.
DOI
https://doi.org/10.2991/cse.2013.5How to use a DOI?
Keywords
clustering, Kohonen Self-Organizing Map (KSOM), tropical wood species
Abstract
This paper discusses on how the Kohonen Self-Organizing Map (KSOM) is used as a tool to cluster and classify the tropical wood species. Wood features have been extracted through the use of two features extractors; Basic Grey Level Aura Matrix (BGLAM) and Statistical Properties of Pores Distribution (SPPD) techniques from the wood images. The wood dataset is trained and tested separately using KSOM algorithm with different parameters such as the number of epochs and map sizes in order to find the best topological network for clustering and classifying the wood data. The clustering results are analyzed and the best result is selected based on common KSOM performance measurement; topological error and quantization error. The number of cluster performed by KSOM is 61 clusters, while the number of overlapped cluster varies for each map. From the results, the 23x23 map size has produced the lowest number of overlapped clusters with the minimum value of topological error and quantization error.
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Proceedings
2nd International Conference on Advances in Computer Science and Engineering (CSE 2013)
Part of series
Advances in Intelligent Systems Research
Publication Date
July 2013
ISBN
978-90786-77-70-3
ISSN
1951-6851
DOI
https://doi.org/10.2991/cse.2013.5How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Ahmad Azlin
AU  - Yusof Rubiyah
PY  - 2013/07
DA  - 2013/07
TI  - Clustering the Tropical Wood Species Using Kohonen Self-Organizing Map (KSOM)
BT  - 2nd International Conference on Advances in Computer Science and Engineering (CSE 2013)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/cse.2013.5
DO  - https://doi.org/10.2991/cse.2013.5
ID  - Azlin2013/07
ER  -