Density Correction Using Multi-Resolution Test Chart
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Solution Overview
Problem
Conventional image forming apparatuses require printing multiple test charts for different resolutions to generate density correction tables, leading to increased errors and decreased accuracy due to environmental or temporal changes in density characteristics.
Innovation Solution
An image processing apparatus and method that uses a single test chart with patch patterns of different resolutions to measure and correct density differences, generating a density correction table that can be applied across various resolutions, thereby simplifying the density adjustment process and maintaining accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple test charts are printed for different resolutions to generate density correction tables, then density correction accuracy can be maintained, but the complexity and time consumption increase significantly
Solution Approach 1:
The patent combines multiple test charts for different resolutions into a single integrated test chart that contains patch patterns representing multiple resolutions. This allows the density correction table to be generated from one test chart instead of requiring separate test charts for each resolution, thereby reducing complexity while maintaining accuracy.
Solution Approach 2:
The single test chart serves multiple functions by incorporating patch patterns for different resolutions within it. This universal test chart can be used to generate density correction tables for all resolutions simultaneously, eliminating the need for separate testing procedures for each resolution.
2Measurement precision
If density correction tables are generated for each resolution separately, then accuracy for each resolution is maintained, but the time required for density adjustment increases
Solution Approach 1:
The patent merges the density correction processes for multiple resolutions into a single operation by using one test chart that contains patch patterns for all resolutions. This allows the density correction table to be generated in one time-consuming printing and measurement operation rather than requiring separate operations for each resolution.
Solution Approach 2:
The test chart is prepared in advance with patch patterns representing multiple resolutions, so that when density correction is needed, the chart is already configured to provide accuracy for all resolutions simultaneously, eliminating the need for time-consuming separate preparation for each resolution.
3Device complexity
If approximation is used to calculate density correction tables from similar density characteristics, then the number of test charts is reduced, but error increases due to environmental or temporal changes
Solution Approach 1:
The patent uses actual measurement feedback from a single test chart that includes patch patterns for multiple resolutions. By measuring the density characteristics from the actual printed test chart and using this feedback to generate the density correction table, the system avoids approximation errors and adapts to current environmental and temporal conditions.
Data Source
AI summary
The image processing apparatus measures a density of a first test chart printed using first pattern data obtained by binarizing multi-value patch pattern data with a first resolution, converts the first pattern data into second pattern data with a second resolution, and measures a density of a second test chart printed using the second pattern data. The apparatus obtains difference correction data for correcting differences between the densities of the first and second test charts, corrects the density of the multi-value patch pattern data with the first resolution based on the difference correction data, and generates test chart data including a first pattern obtained by converting pattern data obtained by binarizing the corrected multi-value patch pattern data into pattern data with the second resolution and a second pattern obtained by binarizing multi-value patch pattern data with the second resolution.