Robust image watermarking using a chirp detection-based technique
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A new robust image watermarking algorithm that embeds multiple watermark bits in the host image is proposed. Linear chirps are embedded as watermark messages, where the slopes of the chirp on the time-frequency (TF) plane represent watermark messages, such that each slope corresponds to a unique message. The Hough-Radon transform (HRT) is a widely used tool to detect directional elements that satisfy a parametric constraint in images. Since linear chirps are localised as a straight line in the TF plane, the HRT is used to detect the watermark messages at the receiver. The HRT acts as an error correcting scheme and robustly estimates the slope of the chirps in the presence of any attacks. It is found that the HRT based detector is able to detect the watermark message accurately when the bit error rate is less than 20%. The robustness of the proposed scheme has been evaluated using the checkmark benchmark attacks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 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