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October 1, 2024

Advancing Quality Control in Printing: An Automated Image Processing Framework for Precision Defect Detection

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Authors

CGChristopher GreeneMAMohammad AlshoulSASamer Abubaker

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Overview

This approach enhances defect detection in printing using image processing, suggesting a new standard for quality control.

Key Points

  • The automated framework improves defect detection accuracy, and enhances overall quality control in printing processes.
  • Using SSIM and pixel-wise comparisons, the method aims to reduce false positives while identifying defects effectively.
  • Employing algorithms for Gaussian smoothing and edge tracking, the process ensures that image analysis is precise and reliable.
  • The research offers significant advancements in quality assessment techniques for the printing sector, promoting efficiency and consistency.

Cite This Study

Greene et al. (2024) studied this question.

synapsesocial.com/papers/68af6595ad7bf08b1eae51dbhttps://doi.org/10.21872/2024iise_7304
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