Image-Based Substrate Permeability Assessment
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Solution Overview
Problem
Traditional methods for determining substrate permeability in printing devices require significant user involvement, lead to printer downtime, and material waste, as they rely on physical testing which may not accurately assess permeability, especially for woven materials that can allow ink to pass through, potentially causing printer damage.
Innovation Solution
A printing device equipped with an image capture device, light source, processor, and machine-readable storage medium that analyzes images of substrates to identify permeability by detecting voids and repeating patterns, comparing them against threshold values, and recommending the use of printing accessories to prevent ink from contacting the print platen if the substrate is permeable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical testing methods are used to determine substrate permeability, then permeability assessment can be obtained, but user involvement increases, printer downtime increases, and material waste increases
Solution Approach 1:
The patent replaces physical testing methods with an image-based analysis system. An image capture device captures images of the substrate, and image processing algorithms analyze the images to determine permeability characteristics such as void content and pattern recognition, eliminating the need for physical printing tests and reducing printer downtime to near zero
Solution Approach 2:
The patent creates a digital copy (image) of the substrate and performs permeability assessment on the copy rather than the original substrate. This allows multiple assessments without physical contact, eliminating material waste and enabling rapid sequential testing
2Measurement precision
If physical testing methods are used to determine substrate permeability, then permeability assessment can be obtained, but user involvement increases and material waste increases
Solution Approach 1:
The system creates a digital replica of the substrate through imaging and performs all analysis on this copy. No physical substrate material is consumed in the testing process, completely eliminating material waste while maintaining assessment accuracy through image-based void detection and pattern analysis
Solution Approach 2:
The patent replaces consumable physical testing methods with a non-contact optical system. Image capture and processing algorithms substitute for physical printing tests, requiring no ink, substrate samples, or other consumable materials
3Productivity
If automated image-based permeability assessment is implemented, then user involvement decreases and printer downtime decreases, but measurement precision may be compromised
Solution Approach 1:
The patent employs sophisticated image processing algorithms including void detection, pattern recognition, and machine learning models to analyze substrate images. These computational methods provide automated, rapid assessment while maintaining high measurement precision through multiple image features being evaluated simultaneously
Solution Approach 2:
The system introduces an image as an intermediary between the substrate and the assessment process. The image capture device creates a detailed visual representation that preserves substrate characteristics, allowing automated analysis to achieve precision comparable to or exceeding physical testing methods
4Productivity
If automated image-based permeability assessment is implemented, then user involvement decreases and material waste decreases, but device complexity increases
Solution Approach 1:
The patent integrates the image capture device, light source, and image processing capabilities into the existing printing device. The same imaging hardware serves multiple functions including substrate permeability assessment, substrate identification, and printing operations, reducing overall system complexity despite the added functionality
Solution Approach 2:
The system performs self-assessment of substrate permeability through automated image capture and analysis. The printing device independently evaluates incoming substrates without requiring external testing equipment or manual intervention, and automatically adjusts printing parameters or recommends accessories based on the assessment results
Data Source
AI summary
Example implementations relate to substrate permeability assessment. Some examples may determine whether voids are shown in an image of a substrate and whether there is a repeating pattern in the image. Some examples may also determine whether printing fluid would pass through the substrate during printing based on the determinations of whether voids are shown in the image and whether there is a repeating pattern in the image.