Taman, Ishak and Md Rosid, Nur Atika and Karis, Mohd Safirin and Hasim, Saipol Hadi and Zainal Abidin, Amar Faiz and Nordin, Nur Anis and Omar, Norhaizat and Jaafar, Hazriq Izzuan and Ab Ghani, Zailani and Hassan, Jefery (2014) Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm. In: International Conference Recent treads in Engineering & Technology (ICRET’2014), 13-14 Feb 2014, Batam (Indonesia).
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Abstract
Woods species recognition is a texture classification difficulty that has been studied by many researchers years ago. The species of the wood are identified by the proposed classification using the textural type that can be observed on the structural features for example the colour of the woods, weight, texture and other features. Any mistakes on texture recognition will affect the economic benefits of wood production where it is an important basis for an identification of woods. Besides, to guide a person to be skilled in wood recognition, it will take a long time and the result the wood sample can be biased. These kinds of problem can be a motivation to develop a system that can recognize the wood effectively. This project will try to integrate both attempts by proposing a classification system consists of feature extractor, classifier and optimizer. The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. For this project, images of wood knot from CAIRO UTM database are used for benchmarking the proposed system performance. The result shows that the proposed approach can perform as good as previous literatures with fewer features used as input for the classifier.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| 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/11673 |
| Statistic Details: | View Download Statistic |
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