PDF OCR Extraction
Extract text from scanned documents and image-based PDFs using OCR technology.
Overview
This skill 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
