Image Resolution Conversion for CAD Line Quality
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Solution Overview
Problem
Conventional image resolution conversion methods for inkjet printing, such as nearest neighbor, averaging, and weighting methods, result in missing image data and reduced line quality, especially when printing CAD drawings with clear black and white lines, and can cause variations in line width due to coordinate-dependent changes in image data after resolution conversion.
Innovation Solution
An image processing method that sets a new top pixel from adjacent pixels when the top pixel has no value, using coefficient calculations based on pixel values to ensure no missing data and consistent line width during resolution conversion from input image to lower resolution, allowing for high-quality printing by maintaining the original number of pixels and line integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the nearest neighbor method is used for resolution conversion, then processing speed is fast, but vertical and horizontal linear missing pixels occur and printing quality lowers significantly
Solution Approach 1:
The patent introduces a new pixel (intermediate element) between the top pixel and the N-th pixel to serve as a mediator. This new pixel is set based on whether missing image data is detected in the range from the top pixel to the N-th pixel. By inserting this intermediary element, the patent prevents the direct transmission of missing pixel defects that occur in the nearest neighbor method while maintaining efficient processing.
Solution Approach 2:
The patent performs preliminary detection of missing image data in the range from the top pixel to the N-th pixel before final resolution conversion. Based on this preliminary detection, it decides whether to set a new pixel to prevent missing data. This preliminary action allows the system to proactively prevent quality issues before they manifest in the final output.
2Manufacturing precision
If the averaging method is used for resolution conversion, then missing image data does not occur, but pixel values of black and white parts are averaged and lines are expressed lighter and bolder so line quality deteriorates
Solution Approach 1:
The patent applies different processing strategies to different local regions based on the detection results. When missing image data is detected, it sets a new pixel with specific characteristics; when no missing data is detected, it uses conventional weighting methods. This local differentiation ensures that line quality is maintained in critical areas while avoiding unnecessary processing in other areas.
Solution Approach 2:
The patent changes the pixel value parameters strategically. Instead of always averaging pixel values (which blurs lines), it conditionally sets new pixel values based on the presence of missing data. This parameter change approach maintains the original pixel value characteristics and line sharpness while preventing missing data artifacts.
3Manufacturing precision
If the weighting method is used for resolution conversion, then missing image data does not occur and line quality is maintained, but the width or height of image data after conversion may change depending on the set of coordinates and a difference is caused between printing results
Solution Approach 1:
The patent enables the resolution conversion system to self-correct coordinate-dependent variations. By detecting missing image data and automatically setting new pixels based on detection results rather than fixed coordinate rules, the system adapts to different coordinate sets and eliminates the inconsistency problem inherent in conventional weighting methods.
Solution Approach 2:
The patent introduces a feedback mechanism where the detection result of missing image data influences the subsequent pixel setting decision. This feedback loop ensures that the resolution conversion process adapts to the actual image content and coordinate characteristics, producing consistent printing results regardless of the input coordinate set.
Data Source
AI summary
An image processing apparatus includes an input unit that inputs printing information containing image data and a conversion unit that, when the pixel value of the top pixel from among successive N pixels (N is an integer equal to or larger than 2) of the image data is a specific value, sets a pixel having a pixel value that is not the specific value as a new top pixel from among pixels from a pixel adjacent to the to pixel to the N-th pixel, refers to data of the new top pixel to the N-th pixel, and performs a conversion into pixel values that are calculated with coefficient values according to the magnitude of the pixel values.