What question did this study set out to answer?

This project aims to develop a system that predicts human blood groups using fingerprint images and deep learning techniques.

May 28, 2026

Blood Group Prediction Using Fingerprint Samples

Key Points

This project aims to develop a system that predicts human blood groups using fingerprint images and deep learning techniques.
Utilized the SOCOFing dataset for preprocessing fingerprints.
Employed a CNN/EfficientNet-B0 model for classifying fingerprints into eight blood groups.
Created a Python interface for users to upload fingerprints and receive predictions.
Demonstrated that fingerprint patterns can support fast blood group screening without laboratory tests.
Achieved classification into eight blood groups with an effective deep learning model.

Abstract

This project develops a non-invasive system to predict human blood group using fingerprint images and deep learning. Fingerprints from the SOCOFing dataset are preprocessed and classified using a CNN/EfficientNet-B0 model into eight blood groups (A+, A−, B+, B−, AB+, AB−, O+, O−). A Python interface enables users to upload a fingerprint and receive an instant prediction, demonstrating that fingerprint patterns can support fast blood group screening without lab tests.

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Cite This Study

M et al. (Tue,) studied this question.

synapsesocial.com/papers/6a17dd4e3fad632b0f9da07e https://doi.org/https://doi.org/10.64388/irev9i11-1718042

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