Statistical texture representation for wood defect image classification using local binary pattern variants
Extensive research has been done on the automation of wood defect detection, to improve the quality of wood products, reduce human labour errors, and increase sales and production, for the wood industry. Our study extends previous work on the automated inspection of wood to include Malaysian wood sp...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/26000/1/Statistical%20texture%20representation%20for%20wood%20defect%20image%20classification%20using%20local%20binary%20pattern%20variants.pdf http://eprints.utem.edu.my/id/eprint/26000/2/Statistical%20texture%20representation%20for%20wood%20defect%20image%20classification%20using%20local%20binary%20pattern%20variants.pdf |
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http://eprints.utem.edu.my/id/eprint/26000/1/Statistical%20texture%20representation%20for%20wood%20defect%20image%20classification%20using%20local%20binary%20pattern%20variants.pdfhttp://eprints.utem.edu.my/id/eprint/26000/2/Statistical%20texture%20representation%20for%20wood%20defect%20image%20classification%20using%20local%20binary%20pattern%20variants.pdf