[1]WU Yiquan,PANG Yaxuan.Research progress of mobile phone surface defect detection based on machine vision[J].CAAI Transactions on Intelligent Systems,2025,20(1):33-51.[doi:10.11992/tis.202312036]
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Research progress of mobile phone surface defect detection based on machine vision

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 20 Number of periods: 2025 1 Page number: 33-51 Column: 综述 Public date: 2025-01-05
Title:
Research progress of mobile phone surface defect detection based on machine vision
Author(s):
WU Yiquan;  PANG Yaxuan
School of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Keywords:
machine vision; defect detection; phone screen glass cover; phone shell; deep learning; data set; performance evaluation index; image processing
CLC:
TP391.41
DOI:
10.11992/tis.202312036
Abstract:
Nowadays, smartphones play an important role in our learning, working, and daily lives. Mass production of smartphones has raised higher requirements for defect detection on the phone surface, including the glass cover and phone shell. Machine vision-based detection methods can achieve faster and more accurate detection of surface defects on smartphones. Taking the challenge in this field as a guide, this paper concludes the research progress of machine vision-based smartphone surface defect detection over the past decade. First, typical defects on the phone surface are listed, and some challenges faced by machine vision in smartphone surface defect detection are analyzed, including algorithm accuracy, real-time performance, and robustness. Then, improvement methods for the above problems are analyzed and compared. In addition, available datasets for smartphone surface defect detection and performance evaluation metrics for algorithms are summarized. Finally, a summary and outlook are provided based on the challenges faced in the field of smartphone surface defect detection.
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