Printed Material Inspection Thresholds for Impurity-Resistant Defect Detection
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Solution Overview
Problem
Existing print inspection systems struggle to set appropriate threshold values for detecting defects without erroneously identifying sheet impurities, as these systems focus solely on defect levels and do not account for variations in impurity characteristics across different sheet types.
Innovation Solution
An apparatus that includes a storage unit for storing a lower limit value of a threshold value and a determination unit to ensure the set threshold value is above this lower limit, preventing impurities from being falsely detected as defects by considering the specific characteristics of each sheet type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a low threshold value is used for defect detection, then detection sensitivity is improved, but false detection of sheet impurities increases
Solution Approach 1:
The system performs preliminary characterization of sheet impurities by analyzing multiple blank sheets and storing statistical information (mean, standard deviation) of impurity pixel values. This preliminary action enables the system to establish a threshold based on actual sheet properties rather than using fixed values, thereby preventing false detection while maintaining sensitivity.
Solution Approach 2:
The system dynamically adjusts the threshold parameter based on the statistical characteristics of sheet impurities. By calculating the mean and standard deviation of impurity pixel values from multiple blank sheets, the system sets the threshold as mean + k×standard deviation, where k is a coefficient. This parameter change adapts the threshold to specific sheet types and conditions.
2Object-affected harmful factors
If a high threshold value is used to avoid false detection, then false detection of sheet impurities is reduced, but detection of actual print defects is compromised
Solution Approach 1:
The system performs preliminary analysis of blank sheets to characterize impurity patterns before actual inspection. By collecting and analyzing impurity data from multiple blank sheets, the system builds a statistical profile that defines the upper boundary of normal variation. This preliminary action ensures the threshold is high enough to filter impurities but low enough to capture real defects.
Solution Approach 2:
The system uses feedback from analyzing blank sheets to refine the threshold setting. By continuously monitoring and analyzing impurity characteristics from multiple blank sheets, the system adjusts the threshold parameter to maintain optimal performance. This feedback mechanism ensures the threshold adapts to changing sheet conditions while maintaining both false positive and false negative rates at acceptable levels.
3Ease of operation
If a fixed threshold value is used, then the inspection process is simple, but it cannot adapt to variations in sheet types and impurity characteristics
Solution Approach 1:
The system performs preliminary characterization of sheet impurities by analyzing multiple blank sheets and storing statistical information. This one-time preliminary action creates a database of impurity patterns that can be reused for subsequent inspections, maintaining operational simplicity while enabling adaptation to different sheet types through stored reference data.
Solution Approach 2:
The system creates a virtual copy of sheet impurity characteristics by analyzing and storing statistical profiles (mean, standard deviation) from multiple blank sheets. Instead of physically analyzing each sheet in detail during inspection, the system uses these pre-generated statistical copies to quickly determine appropriate thresholds, maintaining simplicity while achieving adaptability.
Data Source
AI summary
To make it possible to set an appropriate threshold value for detecting a print defect by taking into consideration an impurity included in a sheet. A lower limit value of a threshold value used for detection of a print defect is found and stored in advance. Then, whether or not a threshold value for detecting a print defect, which is set based on user instructions, is an appropriate threshold value is determined by using the lower limit value stored in advance.