Design of Farthest-Point Masks for Image Halftoning
Why this work is in the frame
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Bibliographic record
Abstract
In an earlier paper, we briefly presented a new halftoning algorithm called farthest-point halftoning. In the present paper, this method is analyzed in detail, and a novel dispersion measure is defined to improve the simplicity and flexibility of the result. This new stochastic screen algorithm is loosely based on Kang's dispersed-dot ordered dither halftone array construction technique used as part of his microcluster halftoning method. Our new halftoning algorithm uses pixelwise measures of dispersion based on one proposed by Kang which is here modified to be more effective. In addition, our method exploits the concept of farthest-point sampling (FPS), introduced as a progressive irregular sampling method by Eldar et al. but uses a more efficient implementation of FPS in the construction of the dot profiles. The technique we propose is compared to other state-of-the-art dither-based halftoning methods in both qualitative and quantitative manners.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it