Make PDF Look Scanned

Add realistic tilt, dirty edges, and noise to your digital PDFs.

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PREVIEW OF PAGE 1
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PDF_TO_SCANNED_CONVERTER_v2.0

CLIENT-SIDE PDF MANIPULATION ENGINE | SCANNER SIMULATION SYSTEM

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$ drag_and_drop | click_to_browse

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TECHNICAL_SPECIFICATIONS

Scanner Effect Parameters

Parameter Data Type Range Default Description
TILT_ANGLE Float 0.0 - 4.0° 1.5° Document rotation angle (simulates crooked scan)
NOISE_LEVEL Integer 0 - 80 25 Scanner dust/grain artifact intensity
BLUR_RADIUS Float 0.0 - 1.5px 0.4px Gaussian blur (ink bleeding effect)
GRAYSCALE Boolean true/false true Monochrome conversion (100% desaturation)
HIGH_CONTRAST Boolean true/false true Contrast boost (120%) + brightness (105%)
SCAN_BORDER Boolean true/false true White scanner bed edges + vignette

Output Quality Matrix

Render Scale Effective DPI File Size Impact Processing Time Use Case
1.0x ~100 DPI Smallest Fastest Web preview, email attachments
2.0x (Default) ~200 DPI Medium Moderate Standard scanned document quality
3.0x ~300 DPI Large Slow High-quality archival scans

Processing Pipeline

1. PDF_PARSE → Extract page bitmap via PDF.js
2. CANVAS_RENDER → Draw to HTMLCanvasElement
3. EFFECT_APPLY → Transform bitmap:
├─ Rotate (tilt angle)
├─ Scale (0.97x if border enabled)
├─ Filter (blur + grayscale + contrast)
├─ Vignette (radial gradient multiply)
└─ Noise overlay (dust/scratch pattern)
4. JPEG_ENCODE → toDataURL('image/jpeg', 0.85)
5. PDF_REBUILD → PDF-Lib embedJpg + addPage
6. METADATA_INJECT → Producer: "HP LaserJet Pro M404"
7. OUTPUT_GENERATE → save() → Uint8Array

System Requirements

  • Modern browser with Canvas API support (Chrome 51+, Firefox 54+, Safari 10+, Edge 79+)
  • JavaScript enabled (no server-side processing available)
  • Minimum 512MB available RAM for PDF processing
  • CORS-enabled environment for CDN library loading
  • PDF.js 3.11.174 (bundled via CDN)
  • PDF-Lib 1.17.1 (bundled via CDN)

FAQ_DATABASE

Do I need to sign up or log in?
No authentication required. Tool operates as static web application with zero backend dependencies. All processing occurs within client browser sandbox using JavaScript Canvas API and WebAssembly-compiled PDF libraries.
Is my data safe?
All files are processed 100% locally in your browser using JavaScript. Zero network transmission of PDF content. No server uploads, no cloud processing, no data persistence. Files exist only in browser memory (volatile RAM) and are garbage-collected upon session termination. GDPR/CCPA compliant by design (no data collection possible).
What file formats are supported?
INPUT: application/pdf (PDF 1.0 - 1.7 specification compliant). OUTPUT: application/pdf with JPEG-encoded page images (DCT compression, quality factor 0.85). Maximum tested file size: 50MB / 500 pages. Browser memory constraints may apply for larger documents.
Can I adjust the scan quality?
Six configurable parameters: (1) Tilt angle [0-4°], (2) Noise intensity [0-80], (3) Blur radius [0-1.5px], (4) Grayscale toggle [boolean], (5) High contrast toggle [boolean], (6) Scanner border toggle [boolean]. Preview function available for real-time parameter tuning on page 1 before full document conversion.
Does it work on mobile devices?
Fully responsive design tested on iOS 14+ (Safari, Chrome) and Android 8+ (Chrome, Firefox, Samsung Internet). Touch-optimized UI with 44x44px minimum touch targets (WCAG 2.1 AA compliant). Performance may vary based on device CPU/GPU capabilities. Recommended minimum: 2GB RAM, quad-core processor for smooth operation on multi-page documents.
What metadata is embedded in the output PDF?
Producer field set to "HP LaserJet Pro M404 / Scanned" to simulate hardware scanner origin. Creator field cleared (empty string). Original PDF metadata (author, title, subject, keywords) is not preserved in output. Creation date set to current timestamp. PDF version: 1.7 (PDF-Lib default).
Can I process password-protected PDFs?
No. Encrypted/password-protected PDFs cannot be processed. PDF.js library requires unencrypted file access for bitmap rendering. Pre-process encrypted files using pdf-password-remover.html tool (if available) before scanning simulation.
How long does processing take?
Performance metrics (Intel Core i5, 16GB RAM, Chrome 120): ~0.5s per page at 2.0x scale. 10-page document: ~5-7 seconds. 100-page document: ~50-70 seconds. Actual time varies by CPU speed, browser JavaScript engine optimization, and selected quality parameters. Noise generation and blur filters are most CPU-intensive operations.

FEATURE_MATRIX

Core Capabilities

  • Client-side PDF parsing and reconstruction (zero server dependency)
  • Multi-page batch processing with progress tracking
  • Real-time preview rendering for parameter optimization
  • Adjustable tilt angle (0-4° rotation with edge preservation)
  • Configurable noise overlay (dust/grain/scratch simulation)
  • Gaussian blur filter (ink bleeding effect)
  • Grayscale conversion (100% desaturation)
  • High contrast enhancement (120% contrast + 105% brightness)
  • Scanner border effects (white edges + corner vignette)
  • JPEG compression for realistic file size reduction
  • Metadata injection (hardware scanner simulation)
  • Drag-and-drop file input interface
  • Keyboard accessible controls (WCAG 2.1 AA compliant)
  • Mobile-responsive UI (320px - 1920px viewport support)
  • Dark mode support (prefers-color-scheme media query)

Browser Compatibility

Security & Privacy

  • Zero network transmission of document content
  • No cookies, no tracking, no analytics of file content
  • Files processed in volatile browser memory (RAM only)
  • No localStorage/IndexedDB persistence of uploaded PDFs
  • Garbage collection automatic upon page unload
  • Subresource Integrity (SRI) for CDN dependencies (recommended)
  • Content Security Policy (CSP) compatible
  • HTTPS deployment recommended (prevents MITM attacks)

API_REFERENCE

applyScanEffectVisual(ctx, width, height)

Core transformation function. Applies scanner simulation effects to Canvas2D rendering context.

async function applyScanEffectVisual(ctx, width, height)

// Parameters:
ctx : CanvasRenderingContext2D // Target canvas context
width : Number // Canvas width in pixels
height : Number // Canvas height in pixels

// Returns: Promise<void>

// Effect Pipeline:
1. captureImageData() → Extract current canvas bitmap
2. fillBackground('#ffffff') → Scanner bed color
3. applyTransform() → Rotate + scale based on tilt/border settings
4. applyFilters() → CSS filter chain (blur, grayscale, contrast)
5. drawTransformed() → Render transformed bitmap
6. applyVignette() → Radial gradient (multiply blend)
7. overlayNoise() → Pattern fill with dust/scratch texture

Performance Optimization Strategies

  • Async/await for non-blocking page processing
  • 20ms setTimeout delays between pages (prevent UI freeze)
  • Canvas memory cleanup (width=1, height=1 after use)
  • Reusable noise pattern canvas (128x128 tiled texture)
  • JPEG quality 0.85 (balance between quality and file size)
  • Progressive progress bar updates (UX feedback)
  • createImageBitmap() for efficient bitmap cloning

SYSTEM_METADATA