Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images

This paper is conducted to explore a new characterization method as a supplement to the traditional roughness characterization. The main research includes the extraction and evaluation of damage features of ceramic surface morphology by applying wavelet methods, the extraction of damage features in...

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Autores principales:	Yanbing Liu, Bei Zhou, Xinghua Yang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Physics QC1-999
Acceso en línea:	https://doaj.org/article/936be1c4241c4a94b12222da7195d5c0
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spelling	oai:doaj.org-article:936be1c4241c4a94b12222da7195d5c02021-11-08T02:36:23ZWavelet Analysis-Based Texture Analysis of Ceramic Surface Images1687-913910.1155/2021/1745135https://doaj.org/article/936be1c4241c4a94b12222da7195d5c02021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/1745135https://doaj.org/toc/1687-9139This paper is conducted to explore a new characterization method as a supplement to the traditional roughness characterization. The main research includes the extraction and evaluation of damage features of ceramic surface morphology by applying wavelet methods, the extraction of damage features in surface contours by using wavelet analysis, and the quantitative evaluation of damage degree by using damage rate and damage mean spacing. By comparing various fractal dimension calculation methods, a fractal dimension method suitable for calculating the ceramic surface was selected, and the fractal method was used to describe the ceramic surface topography as a whole. By comparing different methods of calculating the fractal dimension and further verifying them with the measured three-dimensional morphology, it is found that the vibrational method is more suitable for calculating the fractal dimension of ceramic surface, and its calculation accuracy is investigated, and the results show that the method is a reliable one. Based on the fractal theory, a mathematical model of surface wear and surface sealing was established. Further study of the model shows that the surface with a large fractal dimension has a good sealing effect; the surface corresponding to the best fractal dimension is the most resistant to wear. The fractal method can characterize the complexity of the surface profile as a whole. The wavelet method can describe the ceramic surface profile from a local perspective, and the combination of the two methods can characterize the ceramic surface well. Finally, the experimental device of the ceramic surface defect detection system is constructed, and the joint debugging of hardware and software is completed. Under different light source intensities, ceramic image samples are collected, and the accuracy detection experiments of sample defective edges are conducted, and the results show that the light source has a small impact on the accuracy of ceramic defective edge detection. The results show that the light source has more influence on the accuracy of scratch detection. The results show that the system constructed in this thesis has good applicability for different ceramic sample detection.Yanbing LiuBei ZhouXinghua YangHindawi LimitedarticlePhysicsQC1-999ENAdvances in Mathematical Physics, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physics QC1-999
spellingShingle	Physics QC1-999 Yanbing Liu Bei Zhou Xinghua Yang Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images
description	This paper is conducted to explore a new characterization method as a supplement to the traditional roughness characterization. The main research includes the extraction and evaluation of damage features of ceramic surface morphology by applying wavelet methods, the extraction of damage features in surface contours by using wavelet analysis, and the quantitative evaluation of damage degree by using damage rate and damage mean spacing. By comparing various fractal dimension calculation methods, a fractal dimension method suitable for calculating the ceramic surface was selected, and the fractal method was used to describe the ceramic surface topography as a whole. By comparing different methods of calculating the fractal dimension and further verifying them with the measured three-dimensional morphology, it is found that the vibrational method is more suitable for calculating the fractal dimension of ceramic surface, and its calculation accuracy is investigated, and the results show that the method is a reliable one. Based on the fractal theory, a mathematical model of surface wear and surface sealing was established. Further study of the model shows that the surface with a large fractal dimension has a good sealing effect; the surface corresponding to the best fractal dimension is the most resistant to wear. The fractal method can characterize the complexity of the surface profile as a whole. The wavelet method can describe the ceramic surface profile from a local perspective, and the combination of the two methods can characterize the ceramic surface well. Finally, the experimental device of the ceramic surface defect detection system is constructed, and the joint debugging of hardware and software is completed. Under different light source intensities, ceramic image samples are collected, and the accuracy detection experiments of sample defective edges are conducted, and the results show that the light source has a small impact on the accuracy of ceramic defective edge detection. The results show that the light source has more influence on the accuracy of scratch detection. The results show that the system constructed in this thesis has good applicability for different ceramic sample detection.
format	article
author	Yanbing Liu Bei Zhou Xinghua Yang
author_facet	Yanbing Liu Bei Zhou Xinghua Yang
author_sort	Yanbing Liu
title	Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images
title_short	Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images
title_full	Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images
title_fullStr	Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images
title_full_unstemmed	Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images
title_sort	wavelet analysis-based texture analysis of ceramic surface images
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/936be1c4241c4a94b12222da7195d5c0
work_keys_str_mv	AT yanbingliu waveletanalysisbasedtextureanalysisofceramicsurfaceimages AT beizhou waveletanalysisbasedtextureanalysisofceramicsurfaceimages AT xinghuayang waveletanalysisbasedtextureanalysisofceramicsurfaceimages
_version_	1718443117990903808

Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images

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