International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Blood Group Detection Using Fingerprint Images |
|---|---|
| ABSTRACT | Blood group identification is essential in medical diagnosis, blood transfusion, emergency care, and forensic applications. Conventional blood typing methods are invasive, time-consuming, and dependent on laboratory infrastructure, which can delay critical decisions in emergency or resource-limited environments. To overcome these limitations, this research presents a non-invasive and automated blood group detection system using fingerprint images and deep learning techniques. The proposed system utilizes a Convolutional Neural Network (CNN) based on the ResNet18 architecture to analyse fingerprint patterns and predict blood groups. Fingerprint images are pre-processed through resizing and normalization to ensure uniform input quality. The trained model classifies fingerprints into blood group categories including A+, A−, B+, B−, AB+, AB−, O+, and O−. A Flask-based web application provides a user-friendly interface for real-time blood group prediction. Experimental evaluation demonstrates efficient processing speed and reliable prediction accuracy, confirming the feasibility of fingerprint-based blood group identification. This approach minimizes dependence on traditional blood tests and offers a rapid solution for medical, forensic, and emergency healthcare applications. |
| AUTHOR | ARPIT S B, HEMANTH S MALALI, JEEVAN B G, VINU MATAD, DR. H S SARSWATHI Student, Dept. of IS&E, Jain Institute of Technology, Davanagere, Karnataka, India Associate Professor & Head, Dept. of IS&E, Jain Institute of Technology, Davanagere, Karnataka, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312155 |
| pdf/155_Blood Group Detection Using Fingerprint Images.pdf | |
| KEYWORDS | |
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