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A two-stage defect detection method for unevenly illuminated self-adhesive printed materials.
Peng, Guifeng; Song, Tao; Cao, Songxiao; Zhou, Bin; Jiang, Qing.
Affiliation
  • Peng G; College of Metrology Measurement and Instrument, China Jiliang University, Hangzhou, 310018, China.
  • Song T; College of Metrology Measurement and Instrument, China Jiliang University, Hangzhou, 310018, China. songtao@cjlu.edu.cn.
  • Cao S; College of Metrology Measurement and Instrument, China Jiliang University, Hangzhou, 310018, China.
  • Zhou B; College of Metrology Measurement and Instrument, China Jiliang University, Hangzhou, 310018, China.
  • Jiang Q; College of Metrology Measurement and Instrument, China Jiliang University, Hangzhou, 310018, China.
Sci Rep ; 14(1): 20547, 2024 Sep 04.
Article in En | MEDLINE | ID: mdl-39232131
ABSTRACT
The process of printing defect detection usually suffers from challenges such as inaccurate defect extraction and localization, caused by uneven illumination and complex textures. Moreover, image difference-based defect detection methods often result in numerous small-scale pseudo defects. To address these challenges, this paper proposes a comprehensive defect detection approach that integrates brightness correction and a two-stage defect detection strategy for self-adhesive printed materials. Concretely, a joint bilateral filter coupled with brightness correction corrects uneven brightness properly, meanwhile smoothing the grid-like texture in complex printed material images. Then, in the first detection stage, an image difference method based on a bright-dark difference template group is designed to effectively locate printing defects despite slight brightness fluctuations. Afterward, a discriminative method based on feature similarity is employed to filter out small-scale pseudo-defects in the second detection stage. The experimental results show that the improved difference method achieves an average precision of 99.1% in defect localization on five different printing pattern samples. Furthermore, the second stage reduces the false detection rate to under 0.5% while maintaining the low missed rate.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep / Sci. rep. (Nat. Publ. Group) / Scientific reports (Nature Publishing Group) Year: 2024 Document type: Article Affiliation country: China Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep / Sci. rep. (Nat. Publ. Group) / Scientific reports (Nature Publishing Group) Year: 2024 Document type: Article Affiliation country: China Country of publication: United kingdom