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• W4367183731 endingPage "120241" @default.
• W4367183731 startingPage "120241" @default.
• W4367183731 abstract "First-article inspection of flexographic printing labels (FPLs) is significant before the mass production of FPLs, which is manually implemented by quality check (QC) workers in real industries. In this paper, an adaptive coarse-to-fine framework is proposed for automatic first-article inspection of FPLs based on design drawings, consisting of coarse matching, fine matching, and defect detection. Specifically, a deep learning method integrating SuperPoint and SuperGlue is used for coarse matching between the design drawings and the corresponding FPL image to reveal their inherent characteristics. To deal with local deviations of the characters in the FPL image, a character-wise normalized cross-correlation (NCC) method is proposed to finely align each character in the design drawings with that in the FPL image, which utilizes different searching windows for different characters. Next, a constrained clustering method is proposed to accurately extract the contents of interest (COIs) in the FPL image. Finally, an edge distance measure with an adaptive threshold scheme is proposed to evaluate the COIs for inspection. Comparison experiments show that the proposed framework achieves better inspection performance for first-article inspection of FPLs than other fabric inspection methods. Specifically, it achieves the inspection performance of 1.3% missing rate, 2.0% false rate, and 0.951 Dice at an acceptable inspection speed of 2.735 s/pcs, which demonstrates that it is applicable to facilitate the QC task in real industries." @default.
• W4367183731 created "2023-04-28" @default.
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• W4367183731 date "2023-10-01" @default.
• W4367183731 modified "2023-09-23" @default.
• W4367183731 title "An adaptive coarse-to-fine framework for automatic first article inspection of flexographic printing labels" @default.
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• W4367183731 doi "https://doi.org/10.1016/j.eswa.2023.120241" @default.
• W4367183731 hasPublicationYear "2023" @default.
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