An Approach to Palm-dorsal Vein Recognition Based on Local Gabor Phase Feature
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a new approach to palm-dorsal vein recognition. In contrast to the existing methods, our method employs low-resolution palm-dorsal vein images to achieve effective identification. This method consists of two parts: one part is the palm-dorsal image preprocessing and region of interest (ROI) extraction, the other part is vein feature extraction and verification, using local 2D Gabor phase encoding variance feature to represent the texture feature of the vein image and using histogram to represent the global feature. Chi-square distance is used to evaluate the matching degree. On our own palm-dorsal vein image database, experimental results show that this method achieves 100% acceptance rate and 0% false refuse rate, which indicates the vein pattern biometric is potentially a useful biometric.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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