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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书目详细资料
主要作者:	Rahiddin, Rahillda Nadhirah Norizzaty
格式:	Thesis
语言:	English English
出版:	2021
主题:	Q Science (General)
在线阅读:	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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