Blood Group Prediction Using Finger Print

Authors:

Kattina Jeevan Kowshik, Gogula Akhil, Anakala Naveen Kumar, Lunavath Malsur, Dr. Prajakta Shirke

1,2,3,4CSE Department of Computer Science, Sandip University, Nashik, Maharashtra, India.

5CSE Department of Computer Science, Sandip University, Nashik, Maharashtra, India.

Abstract:

Blood group identification is essential in medical emergencies, transfusion medicine, and forensic investigations. Traditional methods require blood samples and laboratory testing, which can be time-consuming and invasive. This research proposes a non-invasive method for predicting blood groups using fingerprint patterns. Fingerprints are unique biometric identifiers, and prior studies suggest correlations between dermatoglyphic patterns (loops, whorls, arches) and blood groups. This paper presents a system that uses image processing and machine learning techniques to classify fingerprints and predict ABO and Rh blood groups. Experimental results demonstrate moderate predictive accuracy, suggesting the potential of fingerprint-based blood group prediction as a supplementary tool in healthcare and forensic applications.

Keywords:

Blood Group Prediction, Fingerprint Analysis, Dermatoglyphics, Machine Learning, Image Processing, Biometrics