Quick testing approach for evaluating handwriting recognition services with sample images from my Samsung A54.

The Testing Process

Simple three-step methodology for comparing handwriting recognition services:

1. Pick a Sample Image

Using the existing Termux workflow to access camera photos:

# Access latest handwritten sample
ls ~/storage/dcim/Camera/
cp ~/storage/dcim/Camera/$(ls -t ~/storage/dcim/Camera/ | head -1) sample-handwriting.jpg

2. Document Manual Upload Steps

For each online service tested, record:

• Upload method (web interface, API, mobile app)
• Image format requirements
• Authentication requirements

3. Report Back on Results

Compare services on:

• Accuracy - Character recognition rate
• Speed - Processing time
• Usability - Upload workflow complexity
• Cost - Per-image or subscription pricing
• Output format - Plain text, structured data, searchable PDF

Initial Services to Test

• Google Vision API
• Microsoft Azure Cognitive Services
• Amazon Textract
• Apple Live Text (iOS comparison)
• Open-source alternatives (Tesseract, PaddleOCR)

Results and detailed comparisons to follow in subsequent posts.