Image Abnormality Diagnosis Display for Common-Cause Verification
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Solution Overview
Problem
Users may find it difficult to determine the reliability of the cause of image abnormalities in diagnosis results displayed only in association with the abnormalities, leading to potential inaccuracies and increased effort in identifying and addressing the issues.
Innovation Solution
An information processing system that utilizes processors to acquire and display image abnormalities, associating them with their causes, and outputs additional abnormalities with common causes when designated by a user, enhancing reliability through intuitive visual cues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the cause of image abnormality is displayed only in association with the image abnormality, then the display is simple and clear, but the user cannot determine the reliability of the cause
Solution Approach 1:
The patent transitions from a one-to-one display (abnormality-cause pairing) to a many-to-one relationship by displaying multiple abnormalities sharing the same cause. This dimensional change in information organization allows users to assess cause reliability by observing whether multiple independent abnormalities point to the same cause, thereby enhancing reliability without fundamentally complicating the display system.
Solution Approach 2:
The patent segments the display information into two distinct parts: the cause information and the associated abnormalities. By separating these elements and showing the causal relationship explicitly, users can evaluate the reliability of causes by comparing multiple abnormalities that share common causes, thus improving reliability while maintaining display clarity.
2Ease of operation
If multiple image abnormalities are displayed separately, then each abnormality is clearly identified, but the user requires increased effort to determine relationships between abnormalities
Solution Approach 1:
The patent merges multiple abnormalities that share the same cause into a unified display group. By combining these related abnormalities and explicitly showing their common cause, the system preserves all individual abnormality information while simultaneously presenting their relationships, thereby reducing user effort in analysis without losing any relationship information.
Solution Approach 2:
The patent provides feedback by displaying the cause information that connects multiple abnormalities. This feedback mechanism allows users to immediately understand the relationships between abnormalities without requiring additional analysis effort, as the system actively provides the connection information rather than requiring users to discover it themselves.
3Reliability
If the diagnosis result displays only the associated cause for each abnormality, then the display is concise, but the reliability of the cause cannot be determined
Solution Approach 1:
The patent performs preliminary action by pre-calculating and displaying the relationships between multiple abnormalities and their common causes. Instead of requiring users to spend time verifying cause reliability independently, the system has already performed the analysis and presented the results in an easily consumable format, thereby reducing the time users need to invest while enhancing their ability to determine cause reliability.
Data Source
AI summary
An information processing system includes one or a plurality of processors, wherein the one or the plurality of processors acquires a read image that is an image obtained by reading, by a reading section, a diagnosis image of a recording medium output by an image forming section, when the read image has an image abnormality as a result of diagnosis of the read image acquired, displays a cause of the image abnormality in association with the image abnormality, and outputs presence of another image abnormality having the cause being common when at least one of the image abnormality displayed or the cause of the image abnormality is designated by a user.