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A Photovoltaic Image Crack Detection Algorithm Based on Laplacian Pyramid Decomposition

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Communications, Signal Processing, and Systems (CSPS 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 516))

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Abstract

Aiming at detecting cracks in photovoltaic images, a crack detection algorithm of photovoltaic images based on Laplacian pyramid decomposition is studied in this paper. Firstly, in order to suppress noise from the crack area, the image is subjected to a filtering process and contrast enhancement operation. Then, the multi-scale edge detection based on Laplacian pyramid decomposition is applied to the processed image to extract the edge of the image. The results of the extracted fractures are optimized to eliminate the influence of partial noise. Through tests and comparisons, the algorithm is proved effective on crack detection for photovoltaic image.

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References

  1. Yang XN, Huang H, Xiao-Yu XU, et al. Edge extraction based on multi-scale wavelet modulus maxima. J Guizhou Univ, 2013.

    Google Scholar 

  2. Jun WF. Multiscale edge detection based on wavelet modulus maxima. Chin J Sci Instrum, 2006.

    Google Scholar 

  3. Qian B, Tang Z, Xu W. Pavement crack detection based on improved tensor voting. In: International conference on computer science & education. New York: IEEE; 2014. p. 397–402.

    Google Scholar 

  4. Dong HY, Wang L, Li JC, et al. Multiscale edge detection based on Laplacian pyramid. Opto-Electron Eng. 2007;34(7):135–40.

    Google Scholar 

  5. Sandic-Stankovic D, Kukolj D, Callet PL. Image quality assessment based on pyramid decomposition and mean squared error. In: Telecommunications forum telfor. New York: IEEE; 2015. p. 740–3.

    Google Scholar 

  6. Gonzalez RC, Woods et al. Digital image processing. Publishing House of Electronics Industry, 2010.

    Google Scholar 

  7. Ding L, Goshtasby A. On the Canny edge detector. Pattern Recogn. 2001;34(3):721–5.

    Article  Google Scholar 

  8. Jiang HY, Yue-Peng SI, Luo XG. Medical image segmentation based on improved Ostu algorithm and regional growth algorithm. J Northeast Univ. 2006;27(4):398–401.

    Google Scholar 

  9. Zhe LV, Wang FL, Chang YQ, et al. Region-adaptive median filter. J Syst Simul. 2007;19(23):5411–4.

    Google Scholar 

  10. Zou Q, Cao Y, Li Q, et al. CrackTree: Automatic crack detection from pavement images. Pattern Recogn Lett. 2012;33(3):227–38.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Guangdong Testing Institute of Product Quality Supervision, Foshan, 528300, Guangdong, China

    Dai Sui

  2. Information and Technology College, Dalian Maritime University, Dalian, China

    Dongqing Cui

Authors
  1. Dai Sui
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  2. Dongqing Cui
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Corresponding author

Correspondence to Dongqing Cui .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

    Xin Liu

  3. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  4. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Jiasong Mu

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Sui, D., Cui, D. (2020). A Photovoltaic Image Crack Detection Algorithm Based on Laplacian Pyramid Decomposition. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_73

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  • DOI: https://doi.org/10.1007/978-981-13-6504-1_73

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6503-4

  • Online ISBN: 978-981-13-6504-1

  • eBook Packages: EngineeringEngineering (R0)

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