Universiti Teknologi Malaysia Institutional Repository

Using gabor filters as image multiplier for tropical wood species recognition system

Khalid, Marzuki and Yusof, Rubiyah and Rosli, Nenny Ruthfalydia (2010) Using gabor filters as image multiplier for tropical wood species recognition system. In: UKSim-AMSS 12th International Conference on Computer Modelling and Simulation (UKSim 2010), 24-26 Mac 2010, Cambridge, England.

Full text not available from this repository.

Official URL: http://ieeexplore.ieee.org/document/5481196/

Abstract

One of the main problems in wood species recognition systems is the lack of discriminative features of the texture images. In order to overcome this, we use Gabor filter in the pre-processing stage of the wood texture image to multiply the number of features for a single image, thus providing more information for feature extractor to capture. The textural wood features are extracted using two feature extraction methods which are co-occurrence matrix approach, known as grey level co-occurrence matrix (GLCM) and also Gabor filters to generate more variation of features and to improve the accuracy rate. The combined features extracted from GLCM and Gabor filters are sent to the classifier module. A multi-layer neural network based on the popular back propagation (MLBP) algorithm is used for classification. The results show that increasing the number of features by using Gabor filters as image multiplier and the combination of features from Gabor filters and GLCM feature extractors improved the accuracy rate of the wood species recognition system.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:gabor filters, tropical wood
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:24398
Deposited By: Mrs Liza Porijo
Deposited On:19 Sep 2012 02:09
Last Modified:18 Jul 2017 06:33

Repository Staff Only: item control page