Image Inspection Sensitivity Adjustment for Print Defect Detection
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Solution Overview
Problem
Existing automatic inspection systems for print products fail to detect defects near edges or features in print products, leading to inaccurate quality assessment and increased costs due to reliance on visual inspection.
Innovation Solution
An image processing apparatus that sets lower detection sensitivity for defects corresponding to predetermined local patterns in reference images, allowing for more accurate inspection of inspection target images by adjusting detection sensitivities based on region-specific criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a uniform high detection sensitivity is applied across the entire inspection area, then defects in most regions can be detected, but false detections occur near edges and features due to normal printing variations
Solution Approach 1:
The patent applies different detection sensitivities to different regions of the inspection area. Specifically, it sets a first detection sensitivity for a first region (including edges and features) and a second detection sensitivity for a second region (excluding edges and features). This local differentiation allows the system to maintain high detection accuracy in critical areas while avoiding false detections in regions where normal printing variations occur.
2Reliability
If the detection sensitivity is lowered near edges to reduce false detections, then inspection reliability improves, but defect detection accuracy in those regions deteriorates
Solution Approach 1:
The patent divides the inspection area into multiple regions with different detection sensitivity settings. The first region (including edges and features) uses a first detection sensitivity, while the second region (excluding edges and features) uses a second detection sensitivity. This regional differentiation allows the system to optimize detection accuracy in critical areas while maintaining overall inspection reliability.
3Measurement precision
If visual inspection is used to ensure high detection accuracy, then measurement precision improves, but inspection cost and time increase significantly
Solution Approach 1:
The patent replaces manual visual inspection with an automated image processing system that uses algorithms to detect defects. The system acquires an inspection target image, extracts edges and features, divides the area into regions, and applies appropriate detection sensitivities automatically. This substitution maintains high detection accuracy while dramatically improving inspection efficiency and reducing costs.
4Object-generated harmful factors
If the inspection threshold is relaxed near edges to avoid false detections, then false alarm rate decreases, but defect detection capability in those regions is reduced
Solution Approach 1:
The patent implements region-specific detection sensitivity settings where the first region (including edges and features) uses a first detection sensitivity and the second region (excluding edges and features) uses a second detection sensitivity. This approach allows the system to maintain appropriate detection thresholds in different areas, reducing false alarms in edge regions while preserving defect detection capability where needed.
Data Source
AI summary
A detection sensitivity is set such that a detection sensitivity for a defect corresponding to a predetermined local pattern in a reference image, which is a reference printing result, is lower than for a region other than the predetermined local pattern in the reference image. Image data representing an image of an inspection target is acquired and the image of the inspection target is inspected based on the reference image and the set detection sensitivity.