• Laser & Optoelectronics Progress
  • Vol. 58, Issue 24, 2410012 (2021)
Ruhai Zhao1、2、* and Fangbin Wang1、2、3
Author Affiliations
  • 1School of Mechanical and Electrical Engineering, Anhui Jianzhu University, Hefei, Anhui 230601, China
  • 2Key Laboratory of Construction Machinery Fault Diagnosis and Early Warning Technology, Anhui Jianzhu University, Hefei, Anhui 230601, China
  • 3Key Laboratory of Intelligent Manufacturing of Construction Machinery, Anhui Jianzhu University, Hefei, Anhui 230601, China
  • show less
    DOI: 10.3788/LOP202158.2410012 Cite this Article Set citation alerts
    Ruhai Zhao, Fangbin Wang. Polarization Thermal Image Segmentation Algorithm of Metal Fatigue Based on Gray Level and Information Entropy Fusion[J]. Laser & Optoelectronics Progress, 2021, 58(24): 2410012 Copy Citation Text show less
    References

    [1] Kahirdeh A, Khonsari M M. Energy dissipation in the course of the fatigue degradation: mathematical derivation and experimental quantification[J]. International Journal of Solids and Structures, 77, 74-85(2015).

    [2] Wang X G, Ran H R, Jiang C et al. An energy dissipation-based fatigue crack growth model[J]. International Journal of Fatigue, 114, 167-176(2018).

    [3] Naoe T, Xiong Z H, Futakawa M. Temperature measurement for in situ crack monitoring under high-frequency loading[J]. Journal of Nuclear Materials, 506, 12-18(2018).

    [4] Zhu D R, Yang S J, Wang F B et al. Experimental study on texture characteristics of polarized thermography from metal surfaces in fatigue[J]. Laser & Optoelectronics Progress: 1-12[2021-06-07]. https://kns-cnki-net.webvpn.ahjzu.edu.cn/kcms/detail/31.1690.TN.20210524.1751.003.html

    [5] Yi X B, Liang Z F, Shen J C et al. Study on the 304 stainless steel fatigue performance based on the infrared thermal image microscopy observation technology[J]. Chemical Engineering & Machinery, 44, 519-522, 575(2017).

    [6] Wei L X, Yan Z F, Wang W X et al. Study on fatigue crack propagation of AZ31B magnesium alloy based on infrared thermographic technology[J]. Journal of Mechanical Engineering, 48, 64-69(2012).

    [7] Fan J L, Guo X L, Wu C W. Fatigue characterisation based on quantitative infrared thermography[J]. Mechanics in Engineering, 34, 7-17(2012).

    [8] Wang F B, Sun F, Zhu D R et al. Metal fatigue damage assessment based on polarized thermography[J]. Acta Optica Sinica, 40, 1412002(2020).

    [9] Tang Q, Zhang R B, Ling J J et al. Modeling and simulation of thermal emission polarization[J]. Opto-Electronic Engineering, 42, 41-46(2015).

    [10] Corvec G, Robin E, le Cam J B et al. Improving spatio-temporal resolution of infrared images to detect thermal activity of defect at the surface of inorganic glass[J]. Infrared Physics & Technology, 77, 193-202(2016).

    [11] Pozzer S, Rezazadeh Azar E, Dalla Rosa F et al. Semantic segmentation of defects in infrared thermographic images of highly damaged concrete structures[J]. Journal of Performance of Constructed Facilities, 35, 04020131(2021).

    [12] Kabouri A, Khabbazi A, Youlal H. Applied multiresolution analysis to infrared images for defects detection in materials[J]. NDT & E International, 92, 38-49(2017).

    [13] Zhao X L, Zhou P C, Xue M G. A kind of infrared image segment method using improved Chan-Vese model[J]. Infrared Technology, 38, 774-778(2016).

    [14] Jiang Z Z, Han Y S, Xie R C et al. Research on an infrared polarized image fusion algorithm based on NSST transform[J]. Journal of Optoelectronics·Laser, 31, 1140-1148(2020).

    [15] Gong J, Lü J W, Liu L et al. Ship target detection based on infrared polarization image[J]. Spectroscopy and Spectral Analysis, 40, 586-594(2020).

    [16] Yu X L, Chen Q, Gu G H et al. An infared polarization image fusion method based on NSCT and fuzzy C-means clustering segmentation algorithms[J]. Proceedings of SPIE, 9300, 215-223(2014).

    [17] Yi S L, Zhang G F, Chen J. OTSU secondary segmentation algorithm based on information entropy[J]. Journal of Kunming University of Science and Technology (Natural Science), 44, 56-62(2019).

    [18] Yang L, Yang J, Peng N S et al. Weighted information entropy: a method for estimating the complex degree of infrared images’ backgrounds[M]. //Kamel M, Campilho A. Image analysis and recognition. Lecture notes in computer science, 3656, 215-222(2005).

    [19] Yu W J, Gu G H. A polarization image pattern recognition method based on fuzzy C-means clustering and edge detection algorithms[J]. Acta Photonica Sinica, 42, 1244-1247(2013).

    [20] Yang X L, Hou Y Q, Chen S et al. An image segmenting method based on image gray and variance information[J]. Chinese Journal of Quantum Electronics, 27, 677-682(2010).

    [21] Yang L. Study on infrared small target detection and tracking algorithm under complex backgrounds[D](2006).

    [22] Park D C. Intuitive fuzzy C-means algorithm for MRI segmentation[C]. //2010 International Conference on Information Science and Applications, April 21-23, 2010, Seoul, Korea (South)., 11363009(2010).

    [23] Meenakshi S, Suganthi M, Sureshkumar P. Segmentation and boundary detection of fetal kidney images in second and third trimesters using kernel-based fuzzy clustering[J]. Journal of Medical Systems, 43, 1-12(2019).

    [24] Liu J, Li D F. Infrared and visible light image fusion based on Mahalanobis distance and guided filter weighting[J]. Infrared Technology, 43, 162-169(2021).

    [25] Su Q, Yang J Y, Wang Y P. Synthetic aperture radar image change detection based on intuitionistic fuzzy C-core mean clustering algorithm[J]. Laser & Optoelectronics Progress, 56, 192805(2019).

    [26] Ke Y Z, Zhang J W, Sun J Z et al. Image segmentation combining support vector machines with C-means[J]. Journal of Computer Applications, 26, 2081-2083(2006).

    [27] Yang X D, Liu W P. Comparison of algorithms and performance of thresholding and clustering segmentation[J]. Computer Engineering and Application, 50, 183-188, 193(2014).

    [28] Zhang Y J. Image engineering: image processing and analysis[M](1999).

    Ruhai Zhao, Fangbin Wang. Polarization Thermal Image Segmentation Algorithm of Metal Fatigue Based on Gray Level and Information Entropy Fusion[J]. Laser & Optoelectronics Progress, 2021, 58(24): 2410012
    Download Citation