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Open AccessArticle

Feature Extraction with Discrete Non-Separable Shearlet Transform and Its Application to Surface Inspection of Continuous Casting Slabs

by 1, 2,*, 1 and 2
1
National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing 100083, China
2
Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(21), 4668; https://doi.org/10.3390/app9214668
Received: 17 September 2019 / Revised: 11 October 2019 / Accepted: 25 October 2019 / Published: 1 November 2019
(This article belongs to the Special Issue Intelligent Processing on Image and Optical Information)
A new feature extraction technique called DNST-GLCM-KSR (discrete non-separable shearlet transform-gray-level co-occurrence matrix-kernel spectral regression) is presented according to the direction and texture information of surface defects of continuous casting slabs with complex backgrounds. The discrete non-separable shearlet transform (DNST) is a new multi-scale geometric analysis method that provides excellent localization properties and directional selectivity. The gray-level co-occurrence matrix (GLCM) is a texture feature extraction technology. We combine DNST features with GLCM features to characterize defects of the continuous casting slabs. Since the combination feature is high-dimensional and redundant, kernel spectral regression (KSR) algorithm was used to remove redundancy. The low-dimension features obtained and labels data were inputted to a support vector machine (SVM) for classification. The samples collected from the continuous casting slab industrial production line—including cracks, scales, lighting variation, and slag marks—and the proposed scheme were tested. The test results show that the scheme can improve the classification accuracy to 96.37%, which provides a new approach for surface defect recognition of continuous casting slabs. View Full-Text
Keywords: continuous casting slabs; surface defect classification; discrete non-separable shearlet transform; gray-level co-occurrence matrix; kernel spectral regression continuous casting slabs; surface defect classification; discrete non-separable shearlet transform; gray-level co-occurrence matrix; kernel spectral regression
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MDPI and ACS Style

Liu, X.; Xu, K.; Zhou, P.; Liu, H. Feature Extraction with Discrete Non-Separable Shearlet Transform and Its Application to Surface Inspection of Continuous Casting Slabs. Appl. Sci. 2019, 9, 4668.

AMA Style

Liu X, Xu K, Zhou P, Liu H. Feature Extraction with Discrete Non-Separable Shearlet Transform and Its Application to Surface Inspection of Continuous Casting Slabs. Applied Sciences. 2019; 9(21):4668.

Chicago/Turabian Style

Liu, Xiaoming; Xu, Ke; Zhou, Peng; Liu, Huajie. 2019. "Feature Extraction with Discrete Non-Separable Shearlet Transform and Its Application to Surface Inspection of Continuous Casting Slabs" Appl. Sci. 9, no. 21: 4668.

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