Blood Group Prediction Using Fingerprint

Authors

  • Abhishek G L Student, Department of Computer Science and Engineering, PES Institute of Technology, Shivamogga, Karnataka, India
  • Abhishek R Student, Department of Computer Science and Engineering, PES Institute of Technology, Shivamogga, Karnataka, India
  • Mohammed Yasir Makeen Student, Department of Computer Science and Engineering, PES Institute of Technology, Shivamogga, Karnataka, India
  • Hemanth Kumar R Student, Department of Computer Science and Engineering, PES Institute of Technology, Shivamogga, Karnataka, India
  • Suchitha H. S Assistant Professor, Department of Computer Science and Engineering, PES Institute of Technology, Shivamogga, Karnataka, India

Abstract

There is a widespread need worldwide for a cost-effective solution to measure blood groups, especially critical in underprivileged regions. Leveraging Image Processing, a prevalent technology in both affluent and resource-limited areas, presents a viable option for addressing this demand. This project advocates for the use of Image Processing algorithms and detection models to non-invasively ascertain blood groups. Its goal is to offer workable solutions for creating a point-of-care instrument that measures blood group utilizing image processing technologies. The project encompasses outlining various approaches for blood group measurement, recommending strategies for data collection, signal extraction, feature calculation, and implementing Image Processing algorithms to estimate blood groups non-invasively through image analysis.

References

Joshi S, Garg D, Bajaj P, Jindal V. Efficacy of fingerprint to determine gender and blood group. J Dent Oral Care Med. 2016;2(1):103.

Vijaykumar Patil N (2021). A Novel Approach to Predict Blood Group using Fingerprint Map Reading.

Gupta, A., Agarwal, S., & Jain, R. (2019). Blood Group Identification Using Fingerprint Images and Machine Learning Algorithms.

Vijaykumar PN, Ingle DR. A Novel Approach to Predict Blood Group using Fingerprint Map Reading. In2021 6th International Conference for Convergence in Technology (I2CT) 2021 Apr 2 (pp. 1-7). IEEE.

Patil A, Malik A, Shirole T. Fingerprint patterns in relation to gender and blood groups-A study in Navi Mumbai. Indian Journal of Forensic and Community Medicine. 2017 Jul;4(3):204-8.

Smith, J., Johnson, A., & Lee, C. (2020). Fingerprint-Based Biometric Recognition for Blood Group Prediction Using Deep Learning Techniques.

Verma, A., & Bhatt, V. (2018). Automated Blood Group Identification Using Fingerprint Analysis: A Review.

Nandakumar, R., & Subramanian, K. (2017). Blood Group Prediction Using Deep Convolutional Neural Networks.

Gupta, N., Gour, V., & Agarwal, S. (2016). Blood Group Prediction Using Fingerprint Patterns.

Raloti SK, Shah KA, Patel VC, Menat AK, Mori RN, Chaudhari NK. An effort to determine blood group and gender from pattern of finger prints. National Journal of Community Medicine. 2013 Mar 31;4(01):158-60.

Downloads

Published

2024-07-16

Issue

Vol. 9 No. 2 (2023)

Section

Articles