Academic Major Project (B.Tech – Computer Science & Engineering)
Institution: Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad
Year: 2023
Mentor: Dr. Lipika Goel, Associate Professor
Team Members:
- Pavan Karthik (19241A05L6)
- Pradyumna Sinha (19241A05M0)
- Jashwanth Naidu (19241A05J4)
- Anand Thota (19241A05M6)
This repository contains the final major project report completed as part of the Bachelor of Technology in Computer Science and Engineering.
The project focused on developing a real-time sign language recognition system using transfer learning and the TensorFlow Object Detection API.
The goal was to bridge the communication gap between hearing-impaired and normal individuals by recognizing hand gestures from a webcam feed and translating them into corresponding text in real time.
Communication is essential for human interaction, but the hearing-impaired community often faces barriers due to lack of common language understanding.
This project proposes a solution that captures hand gestures via webcam and recognizes them using a deep learning model fine-tuned through Transfer Learning.
By leveraging a pretrained SSD MobileNet V2 model, the system accurately identifies common sign gestures and displays their meanings instantly.
| Tool / Library | Purpose |
|---|---|
| Python 3 | Core programming language |
| OpenCV | Capturing and processing video frames |
| TensorFlow 2.x | Model training and detection |
| NumPy | Array and matrix computations |
| LabelImg | Manual image labeling |
| Jupyter Notebook | Model development and testing |
- Capture sign language gesture images using a webcam
- Label gestures using LabelImg
- Split into training and test datasets
- Convert to TFRecords and create label maps
- Fine-tune SSD MobileNet V2 (COCO) using Transfer Learning
- Perform real-time detection on webcam input
- Detects six basic sign language gestures: Hi, Yes, No, Thank You, Good, I Am Fine
- Demonstrates the effectiveness of Transfer Learning with limited datasets
- Enables a low-cost and accessible method for real-time communication
Pavan Karthik, Pradyumna Sinha, Jashwanth Naidu, Anand Thota.
"Real-Time Sign Language Recognition Using Transfer Learning."
Major Project Report, GRIET, Hyderabad, 2023.
This repository is shared for academic and portfolio purposes only.
All rights are reserved by the original authors and Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad.