Introduction

BrailleVision Hackathon 2026 is centered around one core problem: converting real physical Braille into English using camera-based technology.

Participants should think of this as a computer vision and accessibility challenge, not a simple text translation problem.

A typical system may follow this pipeline:

Camera Input
→ Image Preprocessing
→ Braille Dot Detection
→ Braille Cell Segmentation
→ Braille Pattern Recognition
→ English Text Conversion
→ Text-to-Speech Output

Tools and Technologies

Participants may use any stack. Suggested tools include:

  • Python
  • OpenCV
  • TensorFlow
  • PyTorch
  • MediaPipe
  • Scikit-image
  • NumPy
  • Flask / FastAPI
  • React
  • Flutter
  • Android Studio
  • iOS / Swift
  • Web camera APIs
  • Google ML Kit
  • Text-to-Speech libraries
  • Edge AI or embedded systems

Suggested technical areas:

  • Image processing
  • Computer vision
  • Object detection
  • Dot detection
  • Grid/cell segmentation
  • Perspective correction
  • Lighting normalization
  • Real-time video processing
  • Accessibility-focused UI/UX
  • Speech output
Inspiration

Participants can explore ideas such as:

  • A mobile app that scans Braille and reads it aloud
  • A web app that uses a webcam to detect Braille in real time
  • A Python/OpenCV system that detects raised dots using shadows and contrast
  • An AI model trained to identify Braille cell patterns
  • A low-vision friendly interface with voice instructions
  • A classroom tool for teachers who need to understand Braille worksheets
  • A caregiver tool that helps read physical Braille notes
  • A scanning assistant that guides the user to adjust camera distance and lighting

The most impactful solutions will combine technical accuracy with real accessibility thinking.