Journal of the Korean Physical Society

Korean Physical Society (한국물리학회)
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Accurate Detection of a Defective Area by Adopting a Divide and Conquer Strategy in Infrared Thermal Imaging Measurement

  • Jiangfei, Wang (Key Laboratory of Nondestructive Testing (Ministry of Education), Nanchang Hangkong University) ;
  • Lihua, Yuan (Key Laboratory of Nondestructive Testing (Ministry of Education), Nanchang Hangkong University) ;
  • Zhengguang, Zhu (Key Laboratory of Nondestructive Testing (Ministry of Education), Nanchang Hangkong University) ;
  • Mingyuan, Yuan (Key Laboratory of Nondestructive Testing (Ministry of Education), Nanchang Hangkong University)
  • Received : 2018.06.20
  • Accepted : 2018.08.01
  • Published : 2018.11.30
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Abstract

Aiming at infrared thermal images with different buried depth defects, we study a variety of image segmentation algorithms based on the threshold to develop global search ability and the ability to find the defect area accurately. Firstly, the iterative thresholding method, the maximum entropy method, the minimum error method, the Ostu method and the minimum skewness method are applied to image segmentation of the same infrared thermal image. The study shows that the maximum entropy method and the minimum error method have strong global search capability and can simultaneously extract defects at different depths. However none of these five methods can accurately calculate the defect area at different depths. In order to solve this problem, we put forward a strategy of "divide and conquer". The infrared thermal image is divided into several local thermal maps, with each map containing only one defect, and the defect area is calculated after local image processing of the different buried defects one by one. The results show that, under the "divide and conquer" strategy, the iterative threshold method and the Ostu method have the advantage of high precision and can accurately extract the area of different defects at different depths, with an error of less than 5%.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China, Natural Science Foundation of Jiangxi Province of China, Nanchang Hangkong University

References

  1. P. W. Kruse, Uncooled thermal imaging : arrays, systems, and applications (SPIE Press, 2001).
  2. A. A. Gowen et al., Trends Food Sci. Tech. 21, 190 (2010). https://doi.org/10.1016/j.tifs.2009.12.002
  3. E. F. Ring and K. Ammer, Physiological Measurement 33, R33 (2012). https://doi.org/10.1088/0967-3334/33/3/R33
  4. S. Karmaker, R. Meyers and Y. Shih, Proc SPIE 8518, 851805 (2012).
  5. J. L. Zhong et al. J. Wuhan Univ. Technol. 27, 1180 (2012). https://doi.org/10.1007/s11595-012-0626-9
  6. K. Wang et al. CCDC, IEEE. (Chongqing China, 2017).
  7. X. Yu, Fuz infra. Optik. 140, 959 (2017).
  8. X. Yu et al. Infrared Phy. Tech. 88, 184 (2018). https://doi.org/10.1016/j.infrared.2017.11.029
  9. D. Zhou, H. Zhou and Y. Shao, Infrared Phy. Tech. 74, 81 (2016). https://doi.org/10.1016/j.infrared.2015.12.003
  10. S. R. Neves, E. Silva and G. V. Electron, Electron Lett. 39, 903 (2003). https://doi.org/10.1049/el:20030617
  11. W. Tao and L. Liu, Pattern Recogn Lett. 28, 788 (2007). https://doi.org/10.1016/j.patrec.2006.11.007
  12. R. Raghavendra et al., Pattern Recogn. 44, 401 (2011). https://doi.org/10.1016/j.patcog.2010.08.006
  13. S. S. Alamri, N. V. Kalyankar and S. D. Khamitkar, J. Comput. 2, 83 (2010).
  14. G. Yeo and C. B. Burge, J. Comput Biol. 11, 377 (2003).
  15. S. Laguela et al., Energ Buildings. 43, 1216 (2011). https://doi.org/10.1016/j.enbuild.2010.12.031
  16. B. Feng, Z. Wang and J. Sun, Comput. Engin. Des. 29, 3429 (2008).
  17. F. J. Madruga et al., Ndt & E Int. 43, 661 (2010). https://doi.org/10.1016/j.ndteint.2010.07.002

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