Complete OpenCV Method 3 implementation with 86.5% handwriting retention
- Implemented comprehensive feature analysis based on size, stroke length, and regularity - Size-based scoring: height >50px indicates handwriting - Stroke length ratio: >0.4 indicates handwriting - Irregularity metrics: low compactness/solidity indicates handwriting - Successfully tested on sample PDF with 2 signatures (楊智惠, 張志銘) - Created detailed documentation: CURRENT_STATUS.md and NEW_SESSION_HANDOFF.md - Stable PaddleOCR 2.7.3 configuration documented (numpy 1.26.4, opencv 4.6.0.66) - Prepared research plan for PP-OCRv5 upgrade investigation 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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# 项目当前状态
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**更新时间**: 2025-10-29
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**分支**: `paddleocr-improvements`
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**PaddleOCR版本**: 2.7.3 (稳定版本)
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---
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## 当前进度总结
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### ✅ 已完成
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1. **PaddleOCR服务器部署** (192.168.30.36:5555)
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- 版本: PaddleOCR 2.7.3
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- GPU: 启用
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- 语言: 中文
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- 状态: 稳定运行
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2. **基础Pipeline实现**
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- ✅ PDF → 图像渲染 (DPI=300)
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- ✅ PaddleOCR文字检测 (26个区域/页)
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- ✅ 文本区域遮罩 (padding=25px)
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- ✅ 候选区域检测
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- ✅ 区域合并算法 (12→4 regions)
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3. **OpenCV分离方法测试**
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- Method 1: 笔画宽度分析 - ❌ 效果差
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- Method 2: 连通组件基础分析 - ⚠️ 中等效果
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- Method 3: 综合特征分析 - ✅ **最佳方案** (86.5%手写保留率)
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4. **测试结果**
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- 测试文件: `201301_1324_AI1_page3.pdf`
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- 预期签名: 2个 (楊智惠, 張志銘)
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- 检测结果: 2个签名区域成功合并
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- 保留率: 86.5% 手写内容
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---
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## 技术架构
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```
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PDF文档
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↓
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1. 渲染 (PyMuPDF, 300 DPI)
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↓
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2. PaddleOCR检测 (识别印刷文字)
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↓
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3. 遮罩印刷文字 (黑色填充, padding=25px)
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↓
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4. 区域检测 (OpenCV形态学)
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↓
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5. 区域合并 (距离阈值: H≤100px, V≤50px)
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↓
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6. 特征分析 (大小+笔画长度+规律性)
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↓
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7. [TODO] VLM验证
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↓
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签名提取结果
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```
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---
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## 核心文件
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| 文件 | 说明 | 状态 |
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|------|------|------|
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| `paddleocr_client.py` | PaddleOCR REST客户端 | ✅ 稳定 |
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| `test_mask_and_detect.py` | 基础遮罩+检测测试 | ✅ 完成 |
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| `test_opencv_separation.py` | OpenCV方法1+2测试 | ✅ 完成 |
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| `test_opencv_advanced.py` | OpenCV方法3(最佳) | ✅ 完成 |
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| `extract_signatures_paddleocr_improved.py` | 完整Pipeline (Method B+E) | ⚠️ Method E有问题 |
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| `PADDLEOCR_STATUS.md` | 详细技术文档 | ✅ 完成 |
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---
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## Method 3: 综合特征分析 (当前最佳方案)
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### 判断依据
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**您的观察** (非常准确):
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1. ✅ **手写字比印刷字大** - height > 50px
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2. ✅ **手写笔画长度更长** - stroke_ratio > 0.4
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3. ✅ **印刷体规律，手写潦草** - compactness, solidity
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### 评分系统
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```python
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handwriting_score = 0
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# 大小评分
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if height > 50: score += 3
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elif height > 35: score += 2
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# 笔画长度评分
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if stroke_ratio > 0.5: score += 2
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elif stroke_ratio > 0.35: score += 1
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# 规律性评分
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if is_irregular: score += 1 # 不规律 = 手写
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else: score -= 1 # 规律 = 印刷
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# 面积评分
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if area > 2000: score += 2
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elif area < 500: score -= 1
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# 分类: score > 0 → 手写
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```
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### 效果
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- 手写像素保留: **86.5%** ✅
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- 印刷像素过滤: 13.5%
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- Top 10组件全部正确分类
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---
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## 已识别问题
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### 1. Method E (两阶段OCR) 失效 ❌
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**原因**: PaddleOCR无法区分"印刷"和"手写"，第二次OCR会把手写也识别并删除
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**解决方案**:
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- ❌ 不使用Method E
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- ✅ 使用Method B (区域合并) + OpenCV Method 3
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### 2. 印刷名字与手写签名重叠
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**现象**: 区域包含"楊 智 惠"(印刷) + 手写签名
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**策略**: 接受少量印刷残留，优先保证手写完整性
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**后续**: 用VLM最终验证
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### 3. Masking padding 矛盾
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**小padding (5-10px)**: 印刷残留多，但不伤手写
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**大padding (25px)**: 印刷删除干净，但可能遮住手写边缘
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**当前**: 使用 25px，依赖OpenCV Method 3过滤残留
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---
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## 下一步计划
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### 短期 (继续当前方案)
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- [ ] 整合 Method B + OpenCV Method 3 为完整Pipeline
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- [ ] 添加VLM验证步骤
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- [ ] 在10个样本上测试
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- [ ] 调优参数 (height阈值, merge距离等)
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### 中期 (PP-OCRv5研究)
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**新branch**: `pp-ocrv5-research`
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- [ ] 研究PaddleOCR 3.3.0新API
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- [ ] 测试PP-OCRv5手写检测能力
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- [ ] 对比性能: v4 vs v5
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- [ ] 评估是否升级
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---
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## 服务器配置
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### PaddleOCR服务器 (Linux)
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```
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Host: 192.168.30.36:5555
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SSH: ssh gblinux
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路径: ~/Project/paddleocr-server/
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版本: PaddleOCR 2.7.3, numpy 1.26.4, opencv-contrib 4.6.0.66
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启动: cd ~/Project/paddleocr-server && source venv/bin/activate && python paddleocr_server.py
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日志: ~/Project/paddleocr-server/server_stable.log
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```
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### VLM服务器 (Ollama)
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```
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Host: 192.168.30.36:11434
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模型: qwen2.5vl:32b
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状态: 未在当前Pipeline中使用
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```
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---
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## 测试数据
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### 样本文件
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```
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/Volumes/NV2/PDF-Processing/signature-image-output/201301_1324_AI1_page3.pdf
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- 页面: 第3页
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- 预期签名: 2个 (楊智惠, 張志銘)
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- 尺寸: 2481x3510 pixels
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```
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### 输出目录
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```
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/Volumes/NV2/PDF-Processing/signature-image-output/
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├── mask_test/ # 基础遮罩测试结果
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├── paddleocr_improved/ # Method B+E测试 (E失败)
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├── opencv_separation_test/ # Method 1+2测试
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└── opencv_advanced_test/ # Method 3测试 (最佳)
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```
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---
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## 性能对比
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| 方法 | 手写保留 | 印刷去除 | 总评 |
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|------|---------|---------|------|
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| 基础遮罩 | 100% | 低 | ⚠️ 太多印刷残留 |
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| Method 1 (笔画宽度) | 0% | - | ❌ 完全失败 |
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| Method 2 (连通组件) | 1% | 中 | ❌ 丢失太多手写 |
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| Method 3 (综合特征) | **86.5%** | 高 | ✅ **最佳** |
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---
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## Git状态
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```
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当前分支: paddleocr-improvements
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基于: PaddleOCR-Cover
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标签: paddleocr-v1-basic (基础遮罩版本)
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待提交:
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- OpenCV高级分离方法 (Method 3)
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- 完整测试脚本和结果
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- 文档更新
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```
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---
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## 已知限制
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1. **参数需调优**: height阈值、merge距离等在不同文档可能需要调整
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2. **依赖文档质量**: 模糊、倾斜的文档可能效果变差
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3. **计算性能**: OpenCV处理较快，但完整Pipeline需要优化
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4. **泛化能力**: 仅在1个样本测试，需要更多样本验证
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---
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## 联系与协作
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**主要开发者**: Claude Code
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**协作方式**: 会话式开发
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**代码仓库**: 本地Git仓库
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**测试环境**: macOS (本地) + Linux (服务器)
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---
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**状态**: ✅ 当前方案稳定，可继续开发
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**建议**: 先在更多样本测试Method 3，再考虑PP-OCRv5升级
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