Pattern Recognition Technique for Prediction of Blood Group Using Fingerprint

This paper explores a non-invasive and intelligent technique for predicting an individual’s blood group using fingerprint patterns. Based on dermatoglyphic correlations with the ABO and Rh blood group systems, the method utilizes uploaded fingerprint images, which are processed through image enhancement and machine learning models. The system analyzes fingerprint features such as ridge endings and bifurcations to classify blood groups. This approach aims to enhance healthcare diagnostics, emergency response, and forensic identification through rapid, cost-effective blood group detection. Additionally, this study highlights the increasing demand for biometric-based health solutions, especially in rural or resource-limited settings. The broader implications of this research extend into forensic science, personalized healthcare, and secure identification systems.