Image Inspecting Apparatus Dynamic Threshold Switching
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Solution Overview
Problem
Conventional image inspecting apparatuses face challenges in accurately detecting abnormalities due to the reliance on multiple predetermined spatial filters, which can lead to inappropriate representative value detection.
Innovation Solution
An image inspecting apparatus that acquires read image data and uses an image analyzer to determine abnormalities based on a threshold value, switching between different threshold value calculating methods depending on the number of pixels in a region, ensuring appropriate detection by eliminating edge pixels and using statistical or non-statistical methods for threshold calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple predetermined spatial filters are used to calculate representative values, then abnormality detection capability is provided, but detection accuracy deteriorates due to inappropriate representative value selection
Solution Approach 1:
The patent dynamically switches between different threshold value calculating methods (first method using multiple spatial filters, second method using a different approach) based on the number of pixels in the inspection region. This dynamic adaptation ensures that the appropriate method is selected for each specific imaging condition, resolving the contradiction between providing abnormality detection capability and maintaining detection accuracy.
Solution Approach 2:
The patent changes the parameter of threshold value calculation method based on the pixel count in the inspection region. When the number of pixels is insufficient for reliable statistical analysis, the system switches from the first calculating method to the second method, thereby maintaining detection accuracy across different imaging conditions while preserving abnormality detection capability.
2Measurement precision
If a first threshold value calculating method is used with a region for calculating threshold values, then abnormality detection is performed, but detection reliability deteriorates when the number of pixels in the region is insufficient
Solution Approach 1:
The system dynamically evaluates the number of pixels in the inspection region and switches between the first and second threshold value calculating methods accordingly. This dynamic approach ensures that when pixel count is insufficient, the system transitions to the second method, thereby maintaining abnormality detection reliability while preserving threshold value calculation accuracy.
Solution Approach 2:
The patent implements a feedback mechanism where the system monitors the number of pixels in the inspection region and adjusts the threshold value calculation method based on this information. This feedback loop ensures that the appropriate method is selected to maintain both calculation accuracy and detection reliability under varying imaging conditions.
3Reliability
If multiple spatial filters are applied to calculate representative values, then abnormality detection is enabled, but device complexity increases
Solution Approach 1:
The patent dynamically selects between different processing approaches based on the inspection region characteristics. By switching between the first and second threshold value calculating methods, the system maintains abnormality detection capability while avoiding unnecessary computational complexity when it is not required, thus resolving the contradiction between detection reliability and processing complexity.
Data Source
AI summary
An image inspecting apparatus includes a reader that reads an image on a recording material formed in an image forming apparatus and generates read image data and an image analyzer that performs analysis to determine abnormality for the read image data by using a threshold value and creates an analysis result. The image analyzer makes pixels constituting the read image data a target pixel sequentially and performs determination of abnormality for the target pixel by using the threshold value calculated by using a threshold value calculating method. The threshold value calculating method includes a plurality of threshold value calculating methods, and a first threshold value calculating method is switched to other threshold value calculating method correspondingly to a number of pixels included in a region for calculating a threshold value.