2 - Utilisation de la transformée de Fourier-Mellin pour la reconnaissance de formes multi-orientées et multi-échelles : application à l'analyse automatique de documents techniques
Bibliographic record
Abstract
In this paper, we propose an original methodology which allows the detection and the recognition of multi-oriented and multiscaled patterns. The supports on which the method is applied are technical documents representing the network of the French Telephone operator France Telecom. The adopted technique, based on the Fourier-Mellin Transform (FMT) is integrated in a global strategy that solves ambiguous situations, through the providing of contextual information. The strategy which is applied to solve the character and symbol classification problem can be divided into two stages. The first one consists in computing a set of invariant descriptors for each isolated pattern belonging to a characters layer detected thanks to a connected components extractor. The second stage, based on a filtering scheme, consists in detecting and recognising the shapes which are either interconnected or connected to any other object. The results of the application of this technique are very encouraging since the classification rate reaches excellent scores in comparison with classical techniques.
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How this classification was reachedexpand
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".