# Change: Fix OCR Track Cell Over-Detection

## Why

PP-StructureV3 is over-detecting table cells in OCR Track processing, incorrectly identifying regular text content (key-value pairs, bullet points, form labels) as table cells. This results in:
- 4 tables detected instead of 1 on sample document
- 105 cells detected instead of 12 (expected)
- Broken text layout and incorrect font sizing in PDF output
- Poor document reconstruction quality compared to Direct Track

Evidence from task comparison:
- Direct Track (`cfd996d9`): 1 table, 12 cells - correct representation
- OCR Track (`62de32e0`): 4 tables, 105 cells - severe over-detection

## What Changes

- Add post-detection cell validation pipeline to filter false-positive cells
- Implement table structure validation using geometric patterns
- Add text density analysis to distinguish tables from key-value text
- Apply stricter confidence thresholds for cell detection
- Add cell clustering algorithm to identify isolated false-positive cells

## Root Cause Analysis

PP-StructureV3's cell detection models over-detect cells in structured text regions. Analysis of page 1:

| Table | Cells | Density (cells/10000px²) | Avg Cell Area | Status |
|-------|-------|--------------------------|---------------|--------|
| 1 | 13 | 0.87 | 11,550 px² | Normal |
| 2 | 12 | 0.44 | 22,754 px² | Normal |
| **3** | **51** | **6.22** | **1,609 px²** | **Over-detected** |
| 4 | 29 | 0.94 | 10,629 px² | Normal |

**Table 3 anomalies:**
- Cell density 7-14x higher than normal tables
- Average cell area only 7-14% of normal
- 150px height with 51 cells = ~3px per cell row (impossible)

## Proposed Solution: Post-Detection Cell Validation

Apply metric-based filtering after PP-Structure detection:

### Filter 1: Cell Density Check
- **Threshold**: Reject tables with density > 3.0 cells/10000px²
- **Rationale**: Normal tables have 0.4-1.0 density; over-detected have 6+

### Filter 2: Minimum Cell Area
- **Threshold**: Reject tables with average cell area < 3,000 px²
- **Rationale**: Normal cells are 10,000-25,000 px²; over-detected are ~1,600 px²

### Filter 3: Cell Height Validation
- **Threshold**: Reject if (table_height / cell_count) < 10px
- **Rationale**: Each cell row needs minimum height for readable text

### Filter 4: Reclassification
- Tables failing validation are reclassified as TEXT elements
- Original text content is preserved
- Reading order is recalculated

## Impact

- Affected specs: `ocr-processing`
- Affected code:
  - `backend/app/services/ocr_service.py` - Add cell validation pipeline
  - `backend/app/services/processing_orchestrator.py` - Integrate validation
  - New file: `backend/app/services/cell_validation_engine.py`

## Success Criteria

1. OCR Track cell count matches Direct Track within 10% tolerance
2. No false-positive tables detected from non-tabular content
3. Table structure maintains logical row/column alignment
4. PDF output quality comparable to Direct Track for documents with tables