Universiti Teknologi Malaysia Institutional Repository

Wood species recognition system based on improved basic grey level aura matrix as feature extractor

Paiz Zamri, Mohd. Iza'an and Mohd. Khairuddin, Anis Salwa and Mokhtar, Norrima and Yusof, Rubiyah (2016) Wood species recognition system based on improved basic grey level aura matrix as feature extractor. Journal of Robotics Networking and Artificial Life, 3 (3). pp. 140-143. ISSN 2352-6386

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Official URL: http://www.atlantis-press.com/publications/jrnal/i...

Abstract

An automated wood species recognition system is designed to perform wood inspection at custom checkpoints in order to avoid illegal logging. The system that includes image acquisition, feature extraction and classification is able to classify the 52 wood species. There are 100 images taken from the each wood species is then divided into training and testing samples for classification. In order to differentiate the wood species precisely, an effective feature extractor is necessary to extract the most distinguished features from the wood surface. In this research, an Improved Basic Grey Level Aura Matrix (I-BGLAM) technique is proposed to extract 136 features from the wood image. The technique has smaller feature dimension and is rotational invariant due to the considered significant feature extract from the wood image. Support vector machine (SVM) is used to classify the wood species. The proposed system shows good classification accuracy compared to previous works.

Item Type:Article
Additional Information:RADIS System Ref No:PB/2017/11475
Subjects:T Technology
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Advanced Informatics School
Malaysia-Japan International Institute of Technology
ID Code:66926
Deposited By: Siti Nor Hashidah Zakaria
Deposited On:11 Jul 2017 07:07
Last Modified:20 Nov 2017 08:52

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