gbanyan
2a13f0d985
Respond to a second hostile GPT-5.5 reviewer pass on rev9. Four substantive changes plus accumulated typesetting polish. Reviewer points addressed: - HC != reuse (Fatal 1): new Sec III-F "What HC Means and Does Not Mean" states plainly that HC denotes an extreme within-accountant repetition pattern that is rare between unrelated accountants, not a reuse label; reuse is one interpretation, carried at Firm A by byte-identity + context, never implied by HC alone; no reuse claim is made for Firms B/C/D. - Any-pair construction (Fatal 2): new Table VI gives the per-signature HC flag rate by firm under the deployed any-pair rule vs the strict same-pair rule (cosine and dHash from the same partner). Same-pair lowers all rates but widens the firm gap: Firm A 57.3% vs baseline 5-9%, ratio 2.4-3.4x -> 6.4-10.8x, so the HC region is not an artefact of combining extrema from different pairs. Reproducible via samepair_hc.py (Hamming on stored dHash vectors). - Interviews (Fatal 3): Sec III-A now states the interviews are used only to contextualize, are corroborative not confirmatory and not independently reproducible; their one load-bearing use (Firm A as known-positive benchmark) lowers rather than raises the claim. Empirical claims rest on calibration + byte-identity, which stand without them. - Framing (Fatal 4, rebalance not relabel): contribution 3 elevated to the methodological core (label-free construction/characterization of an operating point without labels), explicitly demonstrated/stress-tested on audit signatures "rather than a finished, fully general framework." The audit finding is kept as a headline result, not demoted to a mere case study, and no general-framework claim is made. Typesetting polish (verified by rendering pages to images): - Unify scientific notation in Table II ([4x10^-6, 2.3x10^-5]). - Tighten Table II row labels to cut excessive wrapping (3 lines -> 2). - Fix duplicated figure captions (empty image alt-text so pandoc no longer auto-captions on top of the hand-written caption); unify caption punctuation. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Qn59FdF9JMyfFg3sjcUNNG
PDF Signature Extraction System
Automated extraction of handwritten Chinese signatures from PDF documents using hybrid VLM + Computer Vision approach.
Quick Start
Step 1: Extract Pages from CSV
cd /Volumes/NV2/pdf_recognize
source venv/bin/activate
python extract_pages_from_csv.py
Step 2: Extract Signatures
python extract_signatures_hybrid.py
Documentation
- PROJECT_DOCUMENTATION.md - Complete project history, all approaches tested, detailed results
- README_page_extraction.md - Page extraction documentation
- README_hybrid_extraction.md - Hybrid signature extraction documentation
Current Performance
Test Dataset: 5 PDF pages
- Signatures expected: 10
- Signatures found: 7
- Precision: 100% (no false positives)
- Recall: 70%
Key Features
✅ Hybrid Approach: VLM name extraction + CV detection + VLM verification
✅ Name-Based: Signatures saved as signature_周寶蓮.png
✅ No False Positives: Name-specific verification filters out dates, text, stamps
✅ Duplicate Prevention: Only one signature per person
✅ Handles Both: PDFs with/without text layer
File Structure
extract_pages_from_csv.py # Step 1: Extract pages
extract_signatures_hybrid.py # Step 2: Extract signatures (CURRENT)
README.md # This file
PROJECT_DOCUMENTATION.md # Complete documentation
README_page_extraction.md # Page extraction guide
README_hybrid_extraction.md # Signature extraction guide
Requirements
- Python 3.9+
- PyMuPDF, OpenCV, NumPy, Requests
- Ollama with qwen2.5vl:32b model
- Ollama instance: http://192.168.30.36:11434
Data
- Input:
/Volumes/NV2/PDF-Processing/master_signatures.csv(86,073 rows) - PDFs:
/Volumes/NV2/PDF-Processing/total-pdf/batch_*/ - Output:
/Volumes/NV2/PDF-Processing/signature-image-output/
Status
✅ Page extraction: Tested with 100 files, working ✅ Signature extraction: Tested with 5 files, 70% recall, 100% precision ⏳ Large-scale testing: Pending ⏳ Full dataset (86K files): Pending
See PROJECT_DOCUMENTATION.md for complete details.