Image Processing Apparatus for Automated Color Precision Assessment
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Solution Overview
Problem
The existing methods for checking the quality of post-color conversion images require extensive manual effort as the number of images increases, especially when color conversion is performed using a machine learning-based model, leading to inefficiencies in identifying images with low color conversion precision.
Innovation Solution
An image processing apparatus that utilizes a processor to generate post-color conversion images using a color conversion model, calculates the color conversion precision, and selectively displays images with precision equal to or less than a threshold, highlighting regions where the precision is below a certain criterion, thereby reducing the manual effort required for quality assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all post-color conversion images are manually checked for quality, then measurement precision of color conversion quality is improved, but loss of time and productivity deteriorate significantly
Solution Approach 1:
The system performs self-assessment of color conversion quality by automatically calculating precision metrics for each image using the color conversion model, eliminating the need for manual checking while maintaining assessment accuracy
Solution Approach 2:
The patent replaces the mechanical manual checking process with an automated computational system that calculates color conversion precision using mathematical formulas and computer algorithms, dramatically reducing time consumption
2Reliability
If all post-color conversion images are manually checked, then reliability of quality assessment is improved, but productivity deteriorates due to enormous manual effort
Solution Approach 1:
The system automatically assesses its own color conversion quality by computing precision metrics, ensuring reliable assessment without requiring manual intervention for each image, thereby maintaining reliability while dramatically improving productivity
Solution Approach 2:
The patent introduces quantitative precision parameters calculated from the color conversion model to objectively assess quality, replacing subjective manual evaluation with measurable parameters that maintain reliability at high speeds
3Measurement precision
If precision calculation is performed for all images, then measurement precision of color conversion is improved, but loss of time deteriorates as the number of images increases
Solution Approach 1:
The system extracts and displays only the low-precision regions that require attention, rather than requiring manual inspection of entire images, maintaining measurement precision while reducing time loss through selective presentation of critical areas
Solution Approach 2:
The patent applies local quality assessment by identifying and highlighting specific regions with low precision rather than requiring uniform manual checking of entire images, enabling efficient focus on critical areas while maintaining overall measurement precision
Data Source
AI summary
An image processing apparatus includes a processor. The processor is configured to execute a program to generate a post-color conversion image from a pre-color conversion image using a color conversion model, calculate a color conversion precision of the post-color conversion image using a precision of the color conversion model, specify a region, the color conversion precision of which is equal to or less than a threshold, and display, of the post-color conversion image, a post-color conversion image, the region of which with the color conversion precision being equal to or less than the threshold has a size that is larger than a criterion determined in advance.