A Novel Approach for Blood Group Identification through Fingerprint Image Analysis

Authors- Akula Venkata Sai Vandana, Adduri Anunay, Daneti Chandana, Anaparthi Harika, Assistant Professor Kaki Leela Prasad

Abstract-The advancements in biometric technology have paved the way for innovative methods of personal identification and data analysis. This project introduces a novel approach for detecting blood groups using fingerprint images, utilizing a comprehensive feature extraction process and advanced classification techniques. Features are extracted from fingerprint images, including geometric and texture-based attributes, and organized into a dataset. These features are analyzed using machine learning techniques, specifically leveraging neural networks, to classify the input fingerprint into its corresponding blood group. The implementation aims to achieve high accuracy and reliability in blood group detection by focusing on feature quality and classifier efficiency. This solution is envisioned as a step forward in integrating biometric data into medical diagnostics and personal identification systems.

DOI: /10.61463/ijset.vol.13.issue1.174