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Evaluation of Scumming Printing Defect by Using Computer Vision-based Bit Plane Slicing Method

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This study demonstrates a computer vision approach to detect scumming defects in printed images, indicating improved efficiency and accuracy.

The automated method achieved high agreement with manual assessments, improving detection of scumming-related issues.
Scumming pixels significantly impact print quality, affecting readability and archival processes during scanning or OCR.
Bit-plane slicing and DCT filtering were employed to effectively isolate scum pixels from print pixels in various image types.
Quantitative metrics for defect severity were established, offering reproducibility and a consistent evaluation mechanism.

Saha et al. (2025) studied this question.

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View Full Paper

Ask AI

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Authors

This study demonstrates a computer vision approach to detect scumming defects in printed images, indicating improved efficiency and accuracy.

The automated method achieved high agreement with manual assessments, improving detection of scumming-related issues.
Scumming pixels significantly impact print quality, affecting readability and archival processes during scanning or OCR.
Bit-plane slicing and DCT filtering were employed to effectively isolate scum pixels from print pixels in various image types.
Quantitative metrics for defect severity were established, offering reproducibility and a consistent evaluation mechanism.

Saha et al. (2025) studied this question.

View Full Paper

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Bookmark