Automatic Classification of Wood Texture using Local Binary Pattern & Fuzzy K-Nearest Neighbor

Mohd Khairuddin, Ismail and Ali, Abuassal and Ali, Abdelrahim and Zainal Abidin, Amar Faiz and Mohamad, Syahrul Hisham and Mutaz, Alsawi and Nordin, Nur Anis and Jaafar, Hazriq Izzuan (2014) Automatic Classification of Wood Texture using Local Binary Pattern & Fuzzy K-Nearest Neighbor. Advanced Material Research, 903. pp. 315-320. ISSN 1022-6680

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Abstract

The price of the wood according to the type of wood. Classification of the woods can be done by studying its texture. This paper introduces Fuzzy k Nearest Neighbor to classify 25 types of wood. The wood’s images have been taken from the Wood Database of the Centre for Artificial Intelligence & Robotics, Universiti Teknologi Malaysia. The features of wood images are extracted using Local Binary Pattern. The results of this paper shows improvement in wood classification compare to the previous literature.

Item Type:	Article
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Electrical Engineering > Department of Control, Instrumentation & Automation
Depositing User:	HAZRIQ IZZUAN JAAFAR
Date Deposited:	06 Mar 2014 04:29
Last Modified:	28 May 2015 04:19
URI:	http://eprints.utem.edu.my/id/eprint/11681
Statistic Details:	View Download Statistic

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