Color Estimation System Using Machine Learning for Ink Separation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In color printing, determining the appropriate ink colors for accurate reproduction of images is time-consuming and skill-dependent, leading to inconsistencies in the printing process due to reliance on human judgment for selecting ink colors.
Innovation Solution
A color estimation system utilizing a correlation model generated through machine learning, which takes image information as input to predict the required ink colors, reducing the need for manual selection and streamlining the separation data generation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an operator manually determines ink colors by confirming the color of printed matter, then the ink colors can be selected based on operational skill, but the process takes time and shows inconsistency depending on operator skill level
Solution Approach 1:
The patent replaces the manual mechanical process of operator visual inspection and judgment with an automated optical measurement system. The measurement unit objectively measures color values of the printed matter, and the determination unit automatically determines ink colors based on measured values and stored correlation data, eliminating dependency on operator skill and reducing time consumption.
Solution Approach 2:
The system enables automatic self-determination of ink colors through programmed algorithms that correlate measured color values with ink color information. The determination unit automatically identifies ink colors without human intervention by comparing measured values against stored reference data, making the process self-sufficient and consistent.
2Adaptability or versatility
If an operator manually determines ink colors, then flexibility in color selection is maintained, but the process shows inconsistency and requires high operational skill
Solution Approach 1:
The patent replaces subjective human judgment with objective automated measurement and determination systems. The measurement unit provides consistent color data, and the determination unit applies uniform algorithms to determine ink colors, ensuring reliable and consistent results across different operations while maintaining adaptability through programmable parameters.
Solution Approach 2:
The system incorporates feedback mechanisms where measured color values are compared against stored reference data and correlation information. The determination unit uses this feedback to automatically adjust and determine ink colors, ensuring consistent and reliable results while adapting to different printing conditions through programmed parameters.
3Adaptability or versatility
If manual determination of ink colors is performed, then the process can handle various color requirements, but it increases the complexity of the separation data generation process
Solution Approach 1:
The patent divides the complex separation data generation process into distinct functional modules: a measurement unit for color measurement, a determination unit for ink color identification, and a separation data generation unit for creating printing data. This segmentation simplifies the overall process by making each module's function clear and automated, reducing operational complexity while maintaining versatility.
Solution Approach 2:
The patent replaces complex manual operations with automated systems. The measurement unit automatically captures color data, the determination unit algorithmically identifies ink colors based on measured values and stored correlations, and the separation data generation unit automatically creates printing data. This substitution reduces process complexity while maintaining the ability to handle various color requirements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables accurate and efficient estimation of ink colors, simplifying the separation data generation process and reducing manufacturing steps, thereby improving the consistency and speed of color printing.
Implementation Method 1
the print color of the printed reference image is estimated based on colors of the inks or a spectral reflectance using a Kubelka-Munk equation
Data Source
AI summary
A color estimation system provided with a correlation memory unit storing a correlation model that accepts an image or information of image, and outputting an ink-color set that is a color combination of inks used in reproducing the image by printing; and a color combination extracting unit that extracts the ink-color set corresponding to a print image, which is an image to be printed, by providing an input of the print image or image information of the print image to the correlation model. The correlation model is generated by performing machine learning that generates a correlation between the image information and the ink-color set such that the ink-color set is outputted based on the image information, using a reference image of which the ink-color set necessary for a printing is known in advance.