Neural Network Printing Result Estimation
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Solution Overview
Problem
Existing printing result estimation techniques based on physical simulation require significant operational resources and time, making real-time operation challenging, especially in environments with limited resources.
Innovation Solution
An image processing apparatus that estimates printing results using two neural networks to learn and reproduce the scattering and bleeding of color materials, allowing for accurate and efficient prediction of printing outcomes with reduced operational requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical simulation of printing process is used to estimate printing result, then measurement precision is improved, but productivity deteriorates due to significant operation time required
Solution Approach 1:
The system performs preliminary learning by scanning actual printing results and storing the relationship between input image data and scanning data in advance. During actual operation, the estimation unit directly retrieves and processes this pre-learned data, avoiding time-consuming physical simulations while maintaining high estimation accuracy.
2Measurement precision
If physical simulation of printing process is used to estimate printing result, then measurement precision is improved, but loss of time increases due to lengthy simulation process
Solution Approach 1:
Instead of performing physical simulations, the system creates a digital copy of the printing process by scanning actual printed images and storing the relationship between input data and output results. The estimation unit then uses this digital copy to rapidly predict printing results without requiring actual physical simulation time.
3Measurement precision
If physical simulation of printing process is used to estimate printing result, then measurement precision is improved, but ease of operation deteriorates in limited resource environments
Solution Approach 1:
The system replaces resource-intensive physical simulations with lightweight data processing operations. By using pre-learned scanning data and simple image processing algorithms, the system achieves accurate estimation with minimal computational resources, making it easily operable even in environments with limited processing power.
Data Source
AI summary
The technique of the present disclosure provides an image processing apparatus for estimating a printing result of image data to be printed with a small amount of operation after the image data is obtained. The apparatus is an image processing apparatus for estimating a printing result to be obtained by printing input image data with a printer, including: an obtaining unit that obtains the input image data; and an estimation unit that estimates the printing result based on the input image data. The estimation unit has been caused to learn scanned image data as correct data, the scanned image data being obtained by reading, with a scanner, a printing result obtained by printing predetermined image data with the printer.