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Solar Cell Surface Defects Detection based on Computer Vision

Volume 13, Number 7, November 2017 - Paper 6  - pp. 1048-1056
DOI: 10.23940/ijpe.17.07.p6.10481056

Xiaoliang Qian, Heqing Zhang, Huanlong Zhang, Yuanyuan Wu, Zhihua Diao, Qing-E Wu, Cunxiang Yang*

School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China

(Submitted on July 25, 2017; Revised on August 30, 2017; Accepted on September 15, 2017)



Abstract:

Various types of defects exist in the solar cell surface because of some uncontrollable factors during the process of production. The solar cell surface defects detection is indispensable for the production of solar cell. The automatic defects detection methods based on computer vision have been widely used because of its convenience, real time and low cost. The state-of-the-art methods of solar cell surface defects detection based on computer vision are reviewed in this paper. Firstly, the typical defects of solar cell surface are summarized. Secondly, the state-of-the-art methods are classified into three categories: local scheme, global scheme and local-global scheme based methods, and separately introduced. Thirdly, the qualitative and exact evaluations of state-of-the-art methods are presented. The main contents of this paper and future development trends are summarized in the end.

 

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