Colorimetric Data Correction for LUT Creation
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Solution Overview
Problem
The existing methods for creating look-up tables (LUTs) for color image conversion, such as RGB to CMY, face challenges due to irregularities in calorimetric data from printing devices, leading to incorrect color tones and gradations in printing results, requiring significant time and effort for correction.
Innovation Solution
A colorimetric-data correcting method that involves printing color patches at defined points in the RGB color space, measuring them with a calorimeter, and correcting the data using correlations between RGB and CMY values to create a reliable conversion table, reducing irregularities and ensuring accurate color conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If LUT is created based on irregular calorimetric data, then LUT creation is completed, but singular points are generated in the LUT data causing regions with incorrect gradations in printing results
Solution Approach 1:
The patent applies preliminary action by detecting irregularities in calorimetric data before creating the LUT, and correcting these irregularities in advance. The system identifies singular points in the measured calorimetric data and corrects them before the LUT generation process, preventing the propagation of errors into the final printing output.
Solution Approach 2:
The patent introduces an intermediary correction process between measurement and LUT creation. A correction unit acts as a mediator that processes the raw calorimetric data, identifying and correcting singular points based on relationships with adjacent data points, thereby producing corrected calorimetric data suitable for LUT generation.
2Manufacturing precision
If modifications are made for each irregular calorimetric data on a pinpoint basis, then color accuracy is improved, but considerable time and effort are required for LUT creation
Solution Approach 1:
The system applies self-service by automatically detecting and correcting irregularities in calorimetric data without requiring manual intervention. The correction unit autonomously identifies singular points and applies corrections based on algorithmic analysis of the data relationships, eliminating the need for time-consuming manual pinpoint modifications.
Solution Approach 2:
The patent changes the parameter of data processing from manual correction to automated correction based on mathematical relationships. By analyzing the relationships between calorimetric data points and automatically identifying deviations, the system transforms the correction process into a parameter-driven automated operation that reduces time and effort.
Data Source
AI summary
Colorimetric data corresponding to corner grid points in an RGB color space, such as grid point P1, is used without correction. For grid points positioned on an edge, such as grid point P2, an average value is calculated for calorimetric data corresponding to a total of three grid points, including a target grid point and two adjacent grid points on the edge. For grid points positioned on a surface, such as grid point P4, an average value is calculated for calorimetric data corresponding to a total of nine grid points, including the target grid point and eight adjacent grid points on the surface. For grid points positioned inside the cube-shaped grid, such as grid point P5, an average value is calculated for calorimetric data corresponding to a total of 27 grid points, including the target grid point and 26 grid points adjacent to the target grid point three-dimensionally.