Inline Sensor Color Matching for Mixed-Color Tone Correction
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Solution Overview
Problem
Existing color matching methods in image forming apparatuses impose a significant burden on users due to the need for frequent color measurement using external colorimeters to account for color changes over time, especially when maintaining accuracy in mixed colors like gray, which requires outputting a wide range of neighboring colors and converting device-dependent RGB values to device-independent Lab values.
Innovation Solution
An image processing apparatus and method that uses an inline sensor to read device-dependent RGB values, correcting tone values based on a threshold for device-independent color differences, reducing the need for external colorimeter measurements by determining color correction based on RGB values and device-independent Lab values, and predicting color changes using a neighboring-color change prediction model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If external colorimeter measurements are performed to ensure accurate color matching, then color accuracy is improved, but user burden and operation complexity increase
Solution Approach 1:
The image forming apparatus performs self-diagnosis and self-correction by using its built-in reading device to measure patches it prints itself. The apparatus automatically detects color changes and corrects tone values without requiring external colorimeters or user intervention, making the system serve itself for color maintenance.
Solution Approach 2:
A chart with patches is introduced as an intermediary medium. The apparatus prints patches on the chart, measures them with its built-in sensor, and uses the measurements to correct color deviations. This intermediary enables the apparatus to perform colorimetry functions that would otherwise require external expensive equipment.
2Reliability
If a wide gamut of neighboring colors is output to ensure color matching accuracy, then color matching reliability is improved, but the number of patches and measurement burden increase
Solution Approach 1:
The system changes the parameter of color space representation by converting device-dependent RGB values to device-independent Lab values. This transformation allows for more efficient color difference calculation and enables the system to achieve reliable color matching with fewer patches by focusing on perceptually uniform color spaces.
Solution Approach 2:
The patent replaces the mechanical/manual process of outputting and measuring many physical patches with an automated computational system. The built-in reading device combined with automated Lab value conversion and tone value correction algorithms substitutes for the manual colorimetry process, reducing the need for numerous physical patches.
3Measurement precision
If device-dependent RGB values are converted to device-independent Lab values for color matching, then color matching accuracy is improved, but processing complexity increases
Solution Approach 1:
The image forming apparatus integrates multiple functions into a single system: it acts as both the printing device and the color measurement device. The built-in reading device performs colorimetry on patches printed by the same apparatus, and the control unit handles both the Lab value conversion and tone value correction, creating a universal self-contained color management system.
Solution Approach 2:
The apparatus performs self-correction by automatically converting its own output RGB values to Lab values and adjusting tone values based on measured deviations. This self-service capability eliminates the need for external color management systems or manual intervention, simplifying the overall system architecture despite the computational processes involved.
4Stability of the object's composition
If frequent color measurements are performed to track color changes over time, then color stability is improved, but time consumption and productivity decrease
Solution Approach 1:
The system implements periodic color matching by automatically measuring patches at regular intervals or after a predetermined number of prints. This periodic self-diagnosis maintains color stability over time without requiring continuous user intervention or frequent manual measurements, optimizing the balance between color accuracy and productivity.
Data Source
AI summary
An image processing apparatus for performing color matching of tone values for a same target color in a first state and a second state, includes circuitry that: acquires, from a first chart based on a first tone value of a target mixed color in the first state, a first color value of a patch corresponding to the first tone value; acquires, from a second chart based on the first tone value in the second state, a second color value of a patch corresponding to the first tone value; and corrects the first tone value such that a mixed color based on the first tone value in the second state becomes the target mixed color, when a color difference between the second color value and the first color value is greater than or equal to a threshold.