Ibrahim, Imanurfatiehah and Khairuddin, Anis Salwa Mohd and Arof, Hamzah and Yusof, Rubiyah and Hanafi, Effariza (2018) Statistical feature extraction method for wood species recognition system. European Journal of Wood and Wood Products, 76 (1). pp. 345-356. ISSN 0018-3768, DOI https://doi.org/10.1007/s00107-017-1163-1.
Full text not available from this repository.Abstract
A cascaded wood species recognition system using simple statistical properties of the wood texture is presented where a total of 24 statistical features are extracted from each wood sample. They are mainly vessel features that allow a broad initial grouping of wood texture using fuzzy logic. Then, a neural network classifier is used to refine the broad grouping into the final wood species classification. The proposed system emulates the classification approach normally taken by human experts when analyzing wood species based on texture. A comprehensive set of experiments was performed on a database composed of 3000 macroscopic images of 30 different wood species to evaluate the effectiveness of the system. Finally, its performance is compared with previous works in terms of classification accuracy.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Classification accuracy; Classification approach; Neural network classifier; Species classification; Species recognition systems; Statistical feature extractions; Statistical features; Statistical properties |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 06 Aug 2019 08:16 |
| Last Modified: | 06 Aug 2019 08:16 |
| URI: | http://eprints.um.edu.my/id/eprint/21836 |
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