Color Tone Matching via Pixel Value Transformation
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Solution Overview
Problem
Existing image processing methods for updating color profiles in image output apparatuses face challenges when a reference color chart cannot be obtained, leading to manual matching processes that are time-consuming and dependent on experience, often resulting in waste due to the need for consecutive output of printed materials to confirm matching results.
Innovation Solution
An image processing apparatus and method that includes a transformation unit to reproduce the color tone of one image output by using data from another, estimating geometric transformation parameters, generating color component value association data, and determining a color tone transformation parameter to transform pixel values, allowing for color tone matching without the need for a reference color chart.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual matching process is used to match color tone without reference color chart, then color tone matching can be achieved, but time consumption increases and productivity decreases
Solution Approach 1:
The patent replaces the manual mechanical matching process with an automated image processing system. The transformation unit automatically transforms pixel values between image output apparatuses using predetermined transformation formulas, eliminating the need for manual observation and adjustment. This substitution of manual operations with automated computational processes resolves the contradiction by maintaining color tone matching capability while dramatically improving productivity.
Solution Approach 2:
The patent changes the parameter representation from human-perceptual color values to standardized pixel value transformations. By using predetermined transformation formulas that operate on pixel values rather than relying on manual color assessment, the system automates the matching process. This parameter transformation approach enables automated processing while maintaining accurate color tone matching, thus resolving the productivity versus reliability contradiction.
2Manufacturing precision
If manual matching process is used to confirm color tone, then color accuracy can be achieved, but waste of printed material increases
Solution Approach 1:
The patent replaces manual visual confirmation of color accuracy with automated pixel value transformation and comparison. The transformation unit uses predetermined formulas to transform pixel values and objectively determine color tone matching, eliminating the need for consecutive printing and manual verification. This substitution reduces printed material waste while maintaining color accuracy through computational rather than empirical verification methods.
Solution Approach 2:
The patent creates a digital transformation model that copies the color characteristics from a reference image output apparatus to the target apparatus through pixel value transformation. Instead of physically printing multiple test samples to verify color accuracy, the system uses digital pixel transformation to predict and achieve color matching. This digital copying approach maintains manufacturing precision while eliminating the material waste associated with physical trial printing.
3Reliability
If manual matching process is used, then color tone can be adjusted, but dependence on operator experience increases and ease of operation decreases
Solution Approach 1:
The patent replaces manual color tone adjustment based on operator experience with automated pixel value transformation using predetermined formulas. The transformation unit automatically performs the adjustments that previously required skilled operators, making the process independent of individual expertise. This substitution maintains color tone adjustment capability while dramatically improving ease of operation by eliminating the need for specialized knowledge.
Solution Approach 2:
The patent enables the image output apparatus to perform color tone matching autonomously without human intervention. The transformation unit automatically transforms pixel values and adjusts color tone based on predetermined transformation relationships, making the system self-sufficient. This self-service capability maintains reliable color tone adjustment while improving ease of operation by removing dependence on operator skill and experience.
Data Source
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AI summary
A image processing apparatus includes a transformation unit that reproduces a color tone of a first output data of an original image data output from a first image output apparatus by using a second output data of the original image data output from a second image output apparatus, an estimating unit that estimates first and second geometric transformation parameters, an associating unit that generates first and second color component value association data, and a determining unit that generates a color tone transformation parameter based on a combination of pixel values in which a pixel value of the first image output data is substantially equivalent to a pixel value of the second image output data.