Bitmap Trapping Method for Color Printer Misregistration
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Solution Overview
Problem
Color printers face issues with misregistration of color planes, leading to objectionable artifacts like white gaps between black text and color backgrounds, which existing bitmap-based trapping methods fail to fully address due to lack of control over trapping depth and inefficiencies in halftone screen vector usage.
Innovation Solution
A method for bitmap-based black trapping that identifies qualified black pixels, estimates continuous tone values for neighboring pixels using halftone screen thresholds, and modifies the halftone pixel bitmap to extend color halftone dots beyond black edges, allowing for controlled depth of trapping by adjusting the neighborhood size around the black pixel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If bitmap-based trapping is performed by evaluating pixels using halftone screen vectors, then color halftone dots can extend beyond black edges to eliminate white gaps, but the method does not control the depth of trapping and requires a relatively large number of scan lines
Solution Approach 1:
The patent segments the trapping operation into distinct phases: first identifying qualified black pixels using a limited number of scan lines, then estimating continuous tone values, and finally modifying only the necessary non-black pixel bitmap planes. This segmentation reduces the number of scan lines required while maintaining trapping precision by focusing computational effort only where needed.
Solution Approach 2:
The patent performs preliminary identification of qualified black pixels before performing the actual trapping modification. By pre-identifying which black pixels qualify for trapping based on their proximity to non-black pixels, the algorithm avoids unnecessary evaluations and reduces the total number of scan lines required, thereby reducing complexity while preserving precision.
2Manufacturing precision
If a large number of scan lines are used to find neighboring cells using halftone screen vectors, then trapping coverage is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies local quality by estimating continuous tone values specifically for non-black pixels within a predetermined window around qualified black pixels, rather than processing the entire image. This localized approach ensures trapping coverage is achieved where needed while minimizing processing time by avoiding unnecessary computations in areas that do not require trapping.
Solution Approach 2:
The patent uses partial action by modifying only the non-black pixel bitmap planes at qualified black pixel locations, rather than reprocessing the entire halftone image. This selective modification achieves the necessary trapping coverage while significantly reducing processing time compared to full-image reprocessing.
3Manufacturing precision
If color is added to black pixels to compensate for misregistration, then white gaps are eliminated, but control over the depth of trapping is lost
Solution Approach 1:
The patent introduces dynamics by making the trapping depth adaptive rather than fixed. The predetermined window size around qualified black pixels can be adjusted to control the depth of trapping, allowing the system to adapt to different printing conditions and requirements. This dynamic approach maintains artifact elimination while providing versatile control over trapping depth.
Data Source
AI summary
Provided are bitmap based trapping methods, apparatus and systems. According to one exemplary method, black trapping color image data is performed by estimating the continuous tone values associated with non-black pixels near a qualified black pixel and subsequently, the estimated continuous tone values are halftoned at the qualified black pixel locations and ORed with the original bitmap data.