DocumentCode
1596884
Title
Surface Image Feature Extraction of Laminated Flooring Based on Texture Analysis
Author
Liu, Bin ; Dong, Xiaochen ; Han, Ning
Author_Institution
Coll. of Eng., Beijing Forestry Univ., Beijing, China
Volume
1
fYear
2011
Firstpage
188
Lastpage
191
Abstract
Extracting surface image features of defective laminated flooring correctly and efficiently is the base of detecting its product quality which makes use of machine vision technology. Through the method of texture analysis, this article applies the Gray Level Co-occurrence Matrix (GLCM) to extract image features from a particular series of multiple defective images of laminated flooring. We acquire four principal eigenvalues that describe image texture, namely the energy, contrast, relevance, entropy. The experimental data show that the four eigenvalues can better reflect and express the main defects of laminated flooring.
Keywords
computer vision; eigenvalues and eigenfunctions; feature extraction; image colour analysis; image texture; matrix algebra; defective laminated flooring; gray level cooccurrence matrix; image texture; machine vision; principal eigenvalue; product quality; surface image feature extraction; texture analysis; Correlation; Eigenvalues and eigenfunctions; Entropy; Feature extraction; Fractals; Gray-scale; Substrates; GLCM; feature extraction; image processing; laminated flooring; texture analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2011 International Conference on
Conference_Location
Zhejiang
Print_ISBN
978-1-4577-0676-9
Type
conf
DOI
10.1109/IHMSC.2011.52
Filename
6038178
Link To Document