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Feature Extraction of Foam Nickel Surface Based on Multi-Scale Texture Analysis.
- Source :
-
Journal of Advanced Computational Intelligence & Intelligent Informatics . Mar2019, Vol. 23 Issue 2, p175-182. 8p. - Publication Year :
- 2019
-
Abstract
- In the foam nickel process, texture is the indicator of foam nickel performance. In order to recognize foam nickel surface defects accurately and provide guidance for production operations, this paper proposes a method for extracting foam nickel image textures based on multi-scale texture analysis. First, nonsubsampled contourlet (NSCT) is used to carry out foam nickel image multi-scale decomposition, and the lowfrequency and high-frequency components following decomposition are used to characterize different defect details. Then, the Haralick eigenvalue, which measures the foam nickel image texture information at each sub-band, is calculated. The KPCA and optimal DAG-SVM are adopted in order to reduce the parameter dimension and clarify defects. Tests are carried out on the foam nickel surface image samples, including crack, scratch, pollution, leakage, and indentation tests. The results indicate that the method proposed in this paper can extract different pieces of detailed texture information and can achieve a defect-identifying accuracy of up to 88.9%. [ABSTRACT FROM AUTHOR]
- Subjects :
- *NICKEL
*FOAM
*EIGENVALUES
*TEXTURE analysis (Image processing)
*MULTISCALE modeling
Subjects
Details
- Language :
- English
- ISSN :
- 13430130
- Volume :
- 23
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Journal of Advanced Computational Intelligence & Intelligent Informatics
- Publication Type :
- Academic Journal
- Accession number :
- 135466694
- Full Text :
- https://doi.org/10.20965/jaciii.2019.p0175