🩸 Blood Group Detection Using Fingerprints

An AI-powered blood group prediction system that analyzes fingerprint images using Deep Learning and Computer Vision techniques. The project aims to explore the relationship between fingerprint patterns and blood groups by training Convolutional Neural Network (CNN) models on fingerprint datasets and providing predictions through an interactive web interface.

---

📌 Project Overview

Traditional blood group identification requires blood sample testing. This project investigates a non-invasive alternative approach by analyzing fingerprint images and predicting blood groups using Deep Learning models.

The system processes uploaded fingerprint images, extracts meaningful patterns through CNN architectures, and predicts the most likely blood group along with confidence scores and visual analysis.

---

🚀 Features

• Upload fingerprint images for analysis
• Automatic image preprocessing
• CNN-based blood group prediction
• Prediction confidence visualization
• Interactive user interface
• Result reporting and analysis
• Deep Learning-powered classification
• Heatmap and visual interpretation support
• Real-time prediction workflow

---

🧠 Technologies Used

Programming Languages

• Python
• JavaScript

Frontend

• HTML5
• CSS3
• JavaScript

AI / Machine Learning

• Deep Learning
• Convolutional Neural Networks (CNN)
• Computer Vision

Libraries

• TensorFlow / Keras
• OpenCV
• NumPy
• Pandas
• Matplotlib
• Scikit-Learn

---

🏗️ System Workflow

1. User uploads fingerprint image
2. Image preprocessing and enhancement
3. Feature extraction using CNN
4. Model prediction
5. Confidence score generation
6. Visualization and reporting
7. Final blood group prediction display

---

📂 Project Structure

blood_group_detection/
│
├── dataset/
│   ├── A+
│   ├── A-
│   ├── B+
│   ├── B-
│   ├── AB+
│   ├── AB-
│   ├── O+
│   └── O-
│
├── models/
│
├── static/
│   ├── css/
│   ├── js/
│   └── images/
│
├── templates/
│
├── uploads/
│
├── results/
│
├── app.py
├── train.py
├── requirements.txt
└── README.md

---

📊 Dataset

The model is trained using fingerprint images categorized into different blood groups.

Supported Blood Groups:

• A+
• A-
• B+
• B-
• AB+
• AB-
• O+
• O-

---

📈 Model Development

The model development pipeline includes:

• Data Collection
• Data Preprocessing
• Image Augmentation
• Feature Extraction
• CNN Training
• Validation
• Testing
• Prediction

---

🖥️ Screenshots

Home Page

Fingerprint Upload

Prediction Result

Analysis Dashboard

---

⚙️ Installation

Clone Repository

git clone https://github.com/Manikumarveldurthi/blood_group_detection.git

Navigate to Project

cd blood_group_detection

Install Dependencies

pip install -r requirements.txt

Run Application

python app.py

---

🎯 Results

• Fingerprint image analysis
• Blood group prediction
• Confidence score generation
• Visualization reports
• Interactive prediction dashboard

---

🔮 Future Enhancements

• Larger fingerprint datasets
• Advanced CNN architectures
• Mobile application integration
• Cloud deployment
• Multi-modal biometric analysis
• Explainable AI (XAI) support
• Real-world clinical validation

---

🎓 Academic Project

Final Year B.Tech Project

Department of Computer Science and Engineering

Puducherry Technological University

---

👨‍💻 Author

Veldurthi Venkata Manikumar

• GitHub: https://github.com/Manikumarveldurthi
• LinkedIn: https://www.linkedin.com/in/veldurthi/
• Email: manikumar0459@gmail.com

---

⭐ Support

If you found this project useful, consider giving it a star.