A High Consistency Color Correction System in an Inkjet Printer
Bibliographic record
Abstract
A variety of sources of variability cause inconsistent color reproduction in Inkjet Printers. Difference in the size of drops ejected, paper type and environmental conditions, to name a few, can lead to big differences in the printed colors. This paper describes a system based on sensing the color shift with respect to pre-determined color targets and compensating for it. The system relies on a combination of several components that work together to provide the best results while minimizing cost and user intervention. The key components are: a built-in sensor tuned to get estimates of ink density in the particular ink/media system, a sensor characterization process, a user triggered calibration process that senses and corrects the color errors and a set of color profiles built in the printer's driver.A periodical calibration of the printer/media system ensures consistent and accurate colors in the output. The performance achieved is currently the leading edge in inkjet printers, enabling color accuracy errors below 4 dEab* maximum, which is at least 50% more accurate than most Inkjet printers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".