Hand Sign Recognition
A computer vision system for real-time hand sign classification.
Overview
Developed a real-time Hand Sign Recognition system capable of identifying and classifying hand gestures.
Methodology
- Computer Vision Techniques: Utilized OpenCV for image pre-processing, including:
- Skin color segmentation.
- Convex Hull generation to outline the hand shape.
- Convexity Defects calculation to count fingers and analyze gestures.
- Classification: Experimented with both heuristic-based approaches (finger counting) and Neural Networks for robust classification of complex signs.
Tech Stack
- OpenCV
- Python
- Machine Learning