Day/Night Image Generation via Pre-Printed Edge Removal and Blur
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Solution Overview
Problem
Existing methods for producing high-quality day/night images require precise front-to-back alignment, which is challenging for single print engine printers, especially when printing on thermo-deformable media, leading to reduced image quality due to misalignment.
Innovation Solution
A method and system that process an image to flip, remove edges, and apply blur based on expected misalignment characteristics, allowing for high-quality day/night image production even with misalignment up to 5 mm, using a single print engine by flipping and reinserting media manually or automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If precise front-to-back alignment is required for high-quality day/night images, then image quality is improved, but device complexity and manufacturing cost increase due to requiring dual print engines or highly accurate mechanical systems
Solution Approach 1:
The patent applies preliminary action by processing the image data before printing to anticipate and compensate for expected misalignment. The system determines expected misalignment characteristics based on media type and printing system properties, then pre-modifies the image (edge removal, blurring) to compensate for anticipated registration errors, eliminating the need for complex mechanical alignment systems
Solution Approach 2:
The patent changes parameters of the printed image by dynamically adjusting edge removal amount and blurriness based on determined misalignment characteristics. This allows the same printing system to produce high-quality day/night images across different media types by modifying image parameters rather than mechanical parameters
2Manufacturing precision
If edge details are preserved in the backlit image, then image clarity is improved, but misalignment becomes more visible and reduces overall image quality
Solution Approach 1:
The patent applies local quality by selectively removing edges and applying blurriness specifically to portions of the image that would be most affected by misalignment, while preserving other image qualities. This localized processing ensures that edge details are retained where alignment is accurate while being suppressed where misalignment would be problematic
Solution Approach 2:
The patent converts the potential harm of visible misalignment into a benefit by using the expected misalignment characteristics to guide selective edge removal and blurring. Rather than simply degrading image quality, the process strategically removes only those elements that would reveal misalignment, thereby improving overall perceived image quality despite registration errors
Data Source
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AI summary
According to one example, there is provided a method of generating a day/night image on a media. The method comprises obtaining an image to be printed as a front-to-back image, printing the obtained image on a first side of the media, processing the obtained image by flipping the image, applying a degree of edge removal, and applying a degree blur. The method further comprises printing the processed image on a reverse side of the media, such that the first printed image and printed modified image are substantially aligned with one another.