Fingerprint Recognition for Personalized Blood Group Identification using CNN: A Review
International Journal of Advanced Trends in Computer Science and Engineering · 2025
Fingerprints are unique and stay the same throughout a person’s life, which makes them reliable for identifying individuals. Interestingly, this uniqueness might also help in determining a person’s blood group. In our project, we explore a non-invasive method of detecting blood types using fingerprint patterns. Instead of taking blood samples, we analyse fingerprint features like ridge frequency and spatial patterns using tools like Gabor filters and image processing techniques. We’ll collect fingerprints from individuals along with their known blood groups, then use deep learning, especially Convolutional Neural Networks your figures. (CNNs), to find patterns that may link fingerprint traits to blood types. This approach could make blood group detection faster, safer, and easier helpful in medical emergencies, forensic investigations, and even everyday healthcare.