Event-Based Defect Highlighting in Image Diagnosis Review
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Solution Overview
Problem
Customer engineers face a burden in comprehending image-quality defects in image forming apparatuses, as existing systems simply display defects without clear differentiation between defect types, requiring manual verification.
Innovation Solution
An image diagnosis system that includes processors to acquire images, detect defects, and switch highlighting based on event conditions, allowing for differentiated display of defect locations and types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If multiple types of defect detection processes are used to detect image defects, then the detection capability is improved, but it becomes difficult to provide a scheme for outputting each image defect with an identifiable detection process type
Solution Approach 1:
The patent segments the defect detection results by associating each detected defect with its specific detection process type through color-coded highlighting. Different detection processes (e.g., dot defect detection, line defect detection) are visually separated by assigning distinct colors to their respective defect highlights, enabling clear identification of which process detected each defect while maintaining comprehensive multi-type detection capability
2Device complexity
If image-quality defects are displayed simply according to defect type, then the display is straightforward, but customer engineers must manually verify each defect by measuring it one by one
Solution Approach 1:
The patent performs preliminary action by automatically measuring and calculating defect characteristics (such as defect size, position, and type) before display. The system pre-processes the defect data to extract key measurement results, then presents these pre-measured values directly in the defect list alongside the visual highlights. This eliminates the need for customer engineers to manually measure each defect, significantly reducing verification time while maintaining simple display structure
Data Source
AI summary
An image diagnosis system includes one or more processors configured to: acquire an image for image diagnosis formed by an image forming apparatus serving as a diagnosis target; detect, from the image for image diagnosis, an image-quality defect in the image for image diagnosis; and perform switching of highlighting of an occurrence location of the detected image-quality defect, the switching being performed on a basis of an event.