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PDF OCR Scanner

Extract text from scanned PDFs using optical character recognition

10 minutes
By communitySource
#pdf#ocr#scan#text-extraction

Someone scanned a 50-page contract and emailed it as a PDF. You can see the text but you can't select, search, or copy anything — it's just an image of text. You need the actual content searchable and editable, not a digital photograph of paper.

Who it's for: legal teams digitizing scanned contracts and court documents, accountants extracting data from scanned receipts and invoices, archivists converting paper document collections to searchable digital format, offices processing scanned mail and faxed documents, researchers digitizing historical documents and records

Example

"Make this scanned 30-page contract searchable and copyable" → OCR-processed PDF with selectable text layer, 98% character accuracy, searchable keywords, extracted text also saved as a separate Word document for editing

CLAUDE.md Template

New here? 3-minute setup guide → | Already set up? Copy the template below.

# PDF OCR Extraction

Extract text from scanned documents and image-based PDFs using OCR technology.

## Overview

This workflow helps you:
- Extract text from scanned documents
- Make image PDFs searchable
- Digitize paper documents
- Process handwritten text (limited)
- Batch process multiple documents

## How to Use

### Basic OCR
```
"Extract text from this scanned PDF"
"OCR this document image"
"Make this PDF searchable"
```

### With Options
```
"Extract text from pages 1-10, English language"
"OCR this document, preserve layout"
"Extract and output as structured data"
```

## Document Types

### OCR Quality by Document Type
| Document Type | Expected Quality | Tips |
|---------------|------------------|------|
| **Typed documents** | ⭐⭐⭐⭐⭐ 95%+ | Best results |
| **Printed books** | ⭐⭐⭐⭐ 90%+ | Watch for aging |
| **Forms** | ⭐⭐⭐⭐ 85%+ | Check boxes may need manual |
| **Tables/Data** | ⭐⭐⭐ 80%+ | Structure may need fixing |
| **Handwritten (neat)** | ⭐⭐ 60-80% | Variable results |
| **Handwritten (cursive)** | ⭐ 30-60% | Often needs manual review |
| **Mixed content** | ⭐⭐⭐ 75%+ | Depends on complexity |

## Output Formats

### Plain Text Extraction
```markdown
## OCR Result: [Document Name]

**Pages Processed**: [X]
**Language**: [Detected/Specified]
**Confidence**: [X]%

---

[Extracted text content here]

---

### Notes
- [Any issues or uncertainties]
- [Characters that may be incorrect]
```

### Structured Extraction
```markdown
## OCR Extraction: [Document Name]

### Document Info
| Field | Value |
|-------|-------|
| Title | [Extracted or inferred] |
| Date | [If found] |
| Author | [If found] |

### Content by Section

#### [Header 1]
[Content under this header]

#### [Header 2]
[Content under this header]

### Tables Found
| Column 1 | Column 2 | Column 3 |
|----------|----------|----------|
| [Data] | [Data] | [Data] |

### Uncertain Text
| Page | Original | Confidence | Possible |
|------|----------|------------|----------|
| 3 | "teh" | 70% | "the" |
| 5 | "l0ve" | 65% | "love" |
```

### Searchable PDF Output
```markdown
## OCR to Searchable PDF

**Source**: [filename.pdf]
**Output**: [filename_searchable.pdf]

### Processing Summary
| Metric | Value |
|--------|-------|
| Pages | [X] |
| Words extracted | [Y] |
| Average confidence | [Z]% |
| Processing time | [T] seconds |

### Quality Report
- [X] pages with 95%+ confidence
- [Y] pages with 80-94% confidence
- [Z] pages with <80% confidence (review recommended)

### Searchability
✅ Document is now text-searchable
✅ Original images preserved
✅ Text layer added behind images
```

## Pre-Processing Tips

### Image Quality Checklist
Before OCR, ensure:
- [ ] **Resolution**: 300 DPI minimum (600 for small text)
- [ ] **Contrast**: Clear black text on white background
- [ ] **Alignment**: Document is straight (not skewed)
- [ ] **Completeness**: No cut-off edges
- [ ] **Cleanliness**: No stains, marks, or shadows

### Common Pre-Processing Steps
| Issue | Solution |
|-------|----------|
| Low resolution | Upscale image first |
| Skewed/rotated | Auto-deskew |
| Poor contrast | Adjust levels/threshold |
| Noise/specks | Apply noise reduction |
| Shadows | Flatten lighting |
| Color document | Convert to grayscale |

## Language Support

### Supported Languages
- **Excellent**: English, Spanish, French, German, Italian
- **Good**: Chinese (Simplified/Traditional), Japanese, Korean
- **Moderate**: Arabic, Hebrew (RTL support), Hindi
- **Basic**: Many others with varying quality

### Multi-Language Documents
```
"OCR this document, detect language automatically"
"Extract text, primary: English, secondary: Chinese"
```

## Handling Specific Content

### Forms and Checkboxes
```markdown
## Form Extraction: [Form Name]

### Field Values
| Field | Value | Confidence |
|-------|-------|------------|
| Name | John Smith | 98% |
| Date | 01/15/2026 | 95% |
| Address | 123 Main St | 92% |

### Checkboxes
| Question | Checked |
|----------|---------|
| Option A | ☑️ Yes |
| Option B | ☐ No |
| Option C | ☑️ Yes |

### Signature
[Signature detected on page X - cannot extract text]
```

### Tables
```markdown
## Table Extraction

### Table 1 (Page 2)
| Header A | Header B | Header C |
|----------|----------|----------|
| Value 1 | Value 2 | Value 3 |
| Value 4 | Value 5 | Value 6 |

**Table confidence**: 85%
**Note**: Column 3 may have alignment issues
```

### Handwritten Text
```markdown
## Handwritten Text Extraction

**Legibility Assessment**: [Good/Fair/Poor]
**Recommended**: Manual review

### Extracted Text (Confidence: 65%)
[Extracted text with uncertain words marked]

### Uncertain Words
| Original | Best Guess | Alternatives |
|----------|------------|--------------|
| [image] | "meeting" | "meeting", "meaning" |
| [image] | "Tuesday" | "Tuesday", "Thursday" |

⚠️ **Low confidence extraction - please verify manually**
```

## Batch Processing

### Batch OCR Job
```markdown
## Batch OCR Processing

**Folder**: [Path]
**Total Documents**: [X]
**Status**: [In Progress/Complete]

### Results
| File | Pages | Confidence | Status |
|------|-------|------------|--------|
| doc1.pdf | 5 | 96% | ✅ Complete |
| doc2.pdf | 12 | 88% | ✅ Complete |
| doc3.pdf | 3 | 72% | ⚠️ Review |
| doc4.pdf | 8 | - | ❌ Failed |

### Issues
- doc3.pdf: Pages 2-3 have handwriting
- doc4.pdf: File corrupted

### Summary
- Successful: [X]
- Need Review: [Y]
- Failed: [Z]
```

## Tool Recommendations

### Cloud Services
- Google Cloud Vision (excellent accuracy)
- Amazon Textract (good for forms)
- Azure Computer Vision (balanced)
- Adobe Acrobat (integrated)

### Desktop Software
- ABBYY FineReader (best accuracy)
- Adobe Acrobat Pro (reliable)
- Readiris (good value)
- Tesseract (free, open source)

### Programming Libraries
- pytesseract (Python + Tesseract)
- EasyOCR (Python, multi-language)
- PaddleOCR (Python, good for Asian languages)

## Limitations

- Cannot guarantee 100% accuracy
- Handwritten text has low accuracy
- Very small text may not extract well
- Decorative fonts are problematic
- Background images reduce quality
- Cannot read text in complex graphics
- Processing time increases with pages
README.md

What This Does

Extract text from scanned documents and image-based PDFs using OCR technology.


Quick Start

Step 1: Create a Project Folder

mkdir -p ~/Documents/PdfOcr

Step 2: Download the Template

Click Download above, then:

mv ~/Downloads/CLAUDE.md ~/Documents/PdfOcr/

Step 3: Start Working

cd ~/Documents/PdfOcr
claude

How to Use

Basic OCR

With Options

Output Format

Plain Text Extraction

Limitations

  • Cannot guarantee 100% accuracy
  • Handwritten text has low accuracy
  • Very small text may not extract well
  • Decorative fonts are problematic
  • Background images reduce quality
  • Cannot read text in complex graphics
  • Processing time increases with pages

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