gbanyan
3672c9343e
Framing softening (per partner tone decision: own the limitation rather than defend the strong claim). Abstract: "Firm heterogeneity is decisive ... consistent with firm-level template-like reuse" -> "The framework surfaces pronounced firm-level heterogeneity ... consistent with firm-level template-like reuse but not independently diagnostic, since descriptor-only data cannot separate reuse from digitisation-pipeline or signing-style homogeneity within a firm; we report it as a scope limitation rather than a mechanism finding." S V-H Limitations: new bullet "Mechanism attribution for the firm-level heterogeneity is not identifiable from descriptor-only data." enumerates three non-mutually-exclusive firm-level mechanisms (template-like reuse / digitisation-pipeline homogeneity / signing-style homogeneity), notes the (cosine, dHash) descriptor pair is by construction indifferent to which mechanism generated a near-identical pair, and lists what additional data would be needed for attribution. S VI Conclusion items (3) and (4): "firm heterogeneity quantification" -> "firm-level heterogeneity surfaced by the framework ... reported as a framework-discriminative observation rather than a mechanism finding"; item (4) expanded from template/stamp/document-production reuse alone to the three-mechanism scope, with explicit "not independently establishing" and S V-H cross-reference. DOCX export fix (export_v3.py): add missing LaTeX-to-Unicode tokens (\checkmark, \lvert/\rvert, \lVert/\rVert, \in, \notin, \max, \min, \log, \ln, \exp, \bullet) that were silently dropping content from Table III rows 2-4 (integer-jitter robustness check marks empty) and Table XVIII drift column (|Delta| empty). Rebuild Paper_A_IEEE_Access_Draft_v3.docx via export_v3.py and install copy as Paper_A_IEEE_Access_Draft_v4.0_20260515.docx (replaces prior pandoc-built v4 DOCX which had empty cells in every table header with LaTeX math and inconsistent column widths). All 43 tables now have non-empty cells with sub/superscript runs. Mirrored in paper_a_v4_combined.md for consistency with the single-file combined source. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.