Off-line recognition of handwritten middle age Persian characters using moment
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, the performance of several moment invariant features combined with various classification methods for the recognition of middle age Persian manuscripts is presented. Specifically, Legendre moments (order 2 to 12), Zernike and pseudo-Zernike moments (order 2 to 15), and the set of invariant moments (ϕ 1 , ϕ 2 , ..., ϕ 7 ) are used as features. These features are computed from four versions of character images; (1) grayscale character images (Set A), (2) semithresholded character images (Set B), (3) binarized character images (Set C), (4) character skeleton (Set D). For classification, we have used the minimum Mean Distance (MMD), k-nearest neighbor (KNN), and Parzen methods. The experiment yielded a 2.86% error rate (97.14% classification rate) with pseudo-Zernike moments on the semithresholded character images (set B).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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