Image Processing Apparatus Defect Exclusion Color Correction
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Solution Overview
Problem
Existing image processing technologies face challenges in reducing the effect of defects on color conversion parameters, leading to inaccuracies in image formation due to non-uniform regions and pixel shortages.
Innovation Solution
An image processing apparatus that performs color conversion on color sample data, detects defects in formed images, excludes defective regions, and corrects color conversion parameters based on defect-free regions to ensure accurate color representation, with a threshold-based mechanism to prevent over-correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color conversion parameters are corrected based on inspection image data containing defects, then color accuracy may be improved through correction, but the correction becomes inaccurate due to the presence of defects in the image data
Solution Approach 1:
The patent segments the image data by dividing it into multiple regions and evaluating each region separately for defects. This allows the system to identify and exclude only the defective regions while retaining usable data from non-defective regions, thereby maintaining correction accuracy despite the presence of some defects in the overall image.
Solution Approach 2:
The patent applies local quality assessment by evaluating defect presence in specific regions of the image rather than treating the entire image uniformly. The system determines whether each region is suitable for correction based on local defect characteristics, allowing selective use of different regions for parameter correction.
2Quantity of substance
If all available image data is used for color conversion parameter correction, then more data is available for accurate correction, but defective regions in the image data reduce the overall accuracy
Solution Approach 1:
The patent divides the image data into multiple regions and evaluates each region's quality separately. This segmentation enables the system to identify defective regions and exclude them from correction calculations, thereby maintaining high accuracy even when a portion of the overall image data is unusable.
Solution Approach 2:
The patent dynamically changes the parameter of data selection by adjusting which regions are included or excluded from correction based on defect detection results. The system modifies the effective dataset used for correction by removing defective regions, thereby optimizing the balance between data quantity and correction accuracy.
3Measurement precision
If defect detection and exclusion processing is added to the correction workflow, then correction accuracy is improved by excluding defective regions, but the processing complexity increases
Solution Approach 1:
The patent performs defect detection as a preliminary action before the color conversion parameter correction process. By identifying and marking defective regions in advance, the system prevents these regions from affecting the correction calculations, thereby improving accuracy without adding complex real-time processing during the correction phase.
Solution Approach 2:
The system performs self-service by automatically detecting defects and excluding problematic regions without requiring manual intervention. The automated defect detection and exclusion mechanism operates independently, reducing the need for complex manual processing while maintaining high correction accuracy.
Data Source
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AI summary
An image processing apparatus includes: an acquiring unit that acquires second raster data generated by reading color sample images formed based on first color sample images of first raster data by an image forming apparatus; a detecting unit that detects a defect present in second color sample images of the second raster data; and a correcting unit that excludes image data of a region where the defect is detected by the detecting unit from the second color sample images, and corrects the color conversion parameters such that a color of each second color sample image formed based on the first raster data by the image forming apparatus comes close to a color corresponding to the first color sample image of the first raster data, based on the second raster data corresponding to a region excluding the region where the defect is detected by the detecting unit, and the first raster data.