Dot Data Generation for Fine Line Reproducibility
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Solution Overview
Problem
Existing image processing and printing technologies face challenges in stabilizing the reproduction of fine lines with low density data, particularly with methods like ordered dither and error diffusion, which often result in broken lines or reduced reproducibility, and require complex threshold adjustments to optimize the ratio of error diffusion and dither methods.
Innovation Solution
A printing apparatus and method that generates dot data by comparing gradation values with thresholds, using error diffusion for low gradation areas and dither methods for high gradation areas, with a coefficient-adjusted approach to control the ratio of dot formation between the two methods, allowing for flexible adjustment and improved image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a dither mask with blue noise characteristic or Bayer dither is applied, then the dispersibility of dot arrangement is excellent and image reproducibility is superior, but fine lines with low density data are broken due to unequal dot intervals and large gaps
Solution Approach 1:
The patent changes the threshold parameters dynamically based on local image characteristics. By calculating the standard deviation of gradation values in a neighborhood and comparing it with a reference value, the system adjusts thresholds to accommodate both fine line regions (low standard deviation) and general image regions (high standard deviation), thereby preventing line breakage while maintaining dot dispersibility
Solution Approach 2:
The patent applies different processing characteristics to different regions of the image based on local properties. By evaluating the standard deviation of gradation values in each pixel's neighborhood, the system identifies fine line regions and applies appropriate threshold adjustments locally, ensuring that fine lines are reproduced continuously while other regions maintain excellent dot arrangement
2Ease of manufacture
If a dither mask with regular pattern such as Bayer dither is applied, then dot arrangement is controlled effectively, but dot intervals change considerably according to the angle and position of line drawings, causing lines to disappear
Solution Approach 1:
The patent dynamically adjusts threshold parameters based on the local standard deviation of gradation values. By comparing the calculated standard deviation with a reference value, the system modifies thresholds to compensate for the angle and position dependencies inherent in regular dither patterns, ensuring consistent line reproduction across different orientations
Solution Approach 2:
The patent introduces dynamic threshold adjustment that adapts to local image characteristics. Instead of using fixed thresholds in a regular dither pattern, the system calculates the standard deviation for each pixel's neighborhood and adjusts thresholds accordingly, making the dot formation process adaptive rather than static
3Reliability
If error diffusion method is used, then fine lines are reproduced better by adjusting threshold values, but it requires complex threshold adjustments and feedback processes to optimize the ratio of error diffusion and dither methods
Solution Approach 1:
The patent uses a straightforward parameter change approach by calculating the standard deviation of gradation values and comparing it with a reference value. This simple comparison mechanism automatically determines the appropriate threshold adjustment without requiring complex feedback loops or iterative optimization processes
Solution Approach 2:
The system performs self-adjustment by automatically calculating local standard deviation and selecting appropriate thresholds based on the comparison with reference values. This eliminates the need for external feedback mechanisms or manual optimization, as the algorithm autonomously adapts to local image characteristics
Data Source
AI summary
A printing apparatus includes a dot data generating section configured to: compare a first threshold which is aligned with a dither mask and a corresponding gradation value which corresponds with the image data which is input; generate the dot data by determining that dots are to be formed in a case where it is determined that the corresponding gradation value exceeds the first threshold and generate the dot data by determining the forming of dots due to application of an error diffusion method by comparing correction data, where error diffusion in the image data is complete, and a second threshold in a case where it is determined that the corresponding gradation value does not exceed the first threshold as a result of the comparing; and diffuse errors, which occur as a result of generating the dot data, to pixels in a predetermined range in the vicinity in both cases.