The Kolmogorov–Sinai Entropy in the Setting of Fuzzy Sets for Atmospheric Corrosion Image Texture Analysis
- Authors: Song Y.1, Zhou B.2, Zhang Y.2, Nie X.3, Ma C.1, Gao Z.1, Xia D.1
- 
							Affiliations: 
							- Tianjin Key Laboratory of Composite and Functional Materials, School of Material Science and Engineering
- CNPC research institute of engineering technology
- Guodian Science and Technology Research Institute
 
- Issue: Vol 54, No 11 (2018)
- Pages: 867-872
- Section: Article
- URL: https://journals.rcsi.science/1023-1935/article/view/189584
- DOI: https://doi.org/10.1134/S1023193518130451
- ID: 189584
Cite item
Abstract
Image analysis gives us a new opportunity in corrosion science. Fuzzy Kolmogorov–Sinai (K–S) entropy is used to quantify the average amount of uncertainty of a dynamical system through a sequence of observations. The fuzzy K–S entropy for horizontal and vertical orientations is sensitive to distribution of corrosion product or corrosion degree, and the entropy values decrease as the corrosion becomes more and more serious. It is concluded that the fuzzy K–S entropy is illustrated as an effective feature for image analysis and corrosion classification.
About the authors
Yang Song
Tianjin Key Laboratory of Composite and Functional Materials, School of Material Science and Engineering
														Email: gaozhiming@tju.edu.cn
				                					                																			                												                	China, 							Tianjin, 300072						
Bing Zhou
CNPC research institute of engineering technology
														Email: gaozhiming@tju.edu.cn
				                					                																			                												                	China, 							Tianjin, 300451						
Yingying Zhang
CNPC research institute of engineering technology
														Email: gaozhiming@tju.edu.cn
				                					                																			                												                	China, 							Tianjin, 300451						
Xinhui Nie
Guodian Science and Technology Research Institute
														Email: gaozhiming@tju.edu.cn
				                					                																			                												                	China, 							Nanjing, 210023						
Chao Ma
Tianjin Key Laboratory of Composite and Functional Materials, School of Material Science and Engineering
														Email: gaozhiming@tju.edu.cn
				                					                																			                												                	China, 							Tianjin, 300072						
Zhiming Gao
Tianjin Key Laboratory of Composite and Functional Materials, School of Material Science and Engineering
							Author for correspondence.
							Email: gaozhiming@tju.edu.cn
				                					                																			                												                	China, 							Tianjin, 300072						
Da-Hai Xia
Tianjin Key Laboratory of Composite and Functional Materials, School of Material Science and Engineering
														Email: gaozhiming@tju.edu.cn
				                					                																			                												                	China, 							Tianjin, 300072						
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