Rotation invariant texture feature based on spatial dependence matrix for timber defect detection

Autor:	Ummi Rabaah Hashim, Mohammad Babrdel Bonab, Siti Zaiton Mohd Hashim, Azah Kamilah Muda
Rok vydání:	2013
Předmět:	Matrix (mathematics) Textural feature business.industry Feature extraction Pattern recognition Artificial intelligence Spatial dependence Invariant (mathematics) Texture feature business Mathematics
Zdroj:	ISDA
DOI:	10.1109/isda.2013.6920754
Popis:	This paper addresses the issue of extracting textural feature for timber defect detection. Statistical features based on spatial dependence matrix are extracted for both classes; clear wood and defect. Instead of using the classical directional matrices, rotation invariant spatial dependence matrix formulation is applied to ensure accurate detection regardless of the timber feed direction. Hotelling T-Squared test is used to measure significance difference of mean between feature distributions of the two classes. The result will give some indication to whether the features extracted are sufficient/good enough to be used in future classification stage.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::387beb97b9f7f7e8d266cdaaedc41182 https://doi.org/10.1109/isda.2013.6920754 Zobrazit plný text záznamu