Statistical texture representation for wood defect image classification using local binary pattern variants

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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書目詳細資料
主要作者:	Rahiddin, Rahillda Nadhirah Norizzaty
格式:	Thesis
語言:	English English
出版:	2021
主題:	Q Science (General)
在線閱讀:	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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