ASL Translator with Python

An innovative computer vision project that translates American Sign Language (ASL) gestures into text using deep learning and real-time video processing.

Project Overview

This ASL translator uses advanced computer vision techniques to capture hand gestures through a webcam, process them using deep learning models, and convert recognized signs into readable text. The project aims to bridge communication gaps and make technology more accessible.

Key Features

• Real-time Recognition: Live webcam feed processing for instant translation
• Deep Learning Model: Custom trained neural network for gesture recognition
• Flask Web Interface: User-friendly web application for easy interaction
• High Accuracy: Optimized model with strong recognition performance
• Scalable Architecture: Modular design for easy expansion to more signs

Technical Implementation

Computer Vision Pipeline

• OpenCV: Real-time video capture and image preprocessing
• Hand Detection: MediaPipe integration for accurate hand landmark detection
• Feature Extraction: Geometric and positional feature analysis

Machine Learning

• TensorFlow/Keras: Deep neural network implementation
• Data Preprocessing: Image normalization and augmentation
• Model Training: Custom dataset with ASL gesture examples
• Optimization: Model compression for real-time performance

Web Application

• Flask Backend: REST API for gesture processing
• Real-time Updates: WebSocket integration for live translation
• Responsive Design: Mobile-friendly interface

Challenges & Solutions

• Lighting Variations: Implemented robust preprocessing to handle different lighting conditions
• Hand Position Variance: Data augmentation techniques to improve model generalization
• Real-time Performance: Model optimization and efficient preprocessing pipeline

Future Enhancements

• Expand vocabulary with more ASL signs
• Multi-hand gesture recognition
• Integration with text-to-speech for complete communication loop
• Mobile app development for broader accessibility

Impact

This project demonstrates the potential of AI and computer vision in creating assistive technologies that can significantly improve communication accessibility for the deaf and hard-of-hearing community.