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Original Article

Intelligent Blood Group Detection Using Image- Based Agglutination Analysis and Deep Learning

  • Paper ID 1065
  • Volume 7, Issue 2
  • Pages 221-228
  • Published Online: March-April 2026
  • 11 Views
Open Access Peer Reviewed Crossref DOI

Authors

  • Dr.M.Somasekar1
  • B.Vinay Sekhar2
  • Reddy Manikanta3

1 Professor, Department of ECE, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India. 2 3 Student, Department of ECE, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India.

Article Information

Published Online
March-April 2026
Pages
221-228
Article Type
Original Article
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References

T. Gupta, "Artificial Intelligence and Image Processing Techniques for Blood Group Prediction", 2024 IEEE International Conference
on Computing, Power and Communication Technologies (IC2PCT), Greater Noida, India, 2024, pp.1022-1028,
doi:10.1109/IC2PCT60090.2024.10486628
2. K.R. Reddy, G. Indrani, N. P. Kumar, and K. Vamshi Krishna, "Image based system for Blood Group Classification," International
Conference on Intelligent Computing and Control Systems (ICICCS), Erode, India, 2025, pp. 1308-1313, doi:
10.1109/ICICCS65191.2025.10985254.
3. G. C. Reddy, G. SaiKrishna and A. A. Micheal, "Automated Blood Group Detection System Using Image Processing for Non- invasive
Antigen Feature Extraction and Classification," 2025 3rd International Conference on Intelligent Data Communication Technologies
and Internet of Things (IDCIoT), Bengaluru, India, 2025, pp. 2199 - 2208, doi: 10.1109/IDCIOT64235.2025.10914768
4. K. A. Rashmi, T. Chethana, K. S. Divya Shree, M. Divya and G. Amber, "Blood Group Detection Using Fingerprint," in: 2025
International Conference on Knowledge Engineering and Communication Systems (ICKECS), Chickballapur, India, 2025, pp. 1-7, doi10.1109/ICKECS65700.2025.11034795.
5. G. Ramkumar, N. J. Rao, V. Nanammal, S. Shaphiya, J. Giri and A. A. A. Samhan, "Empirical Assessment of Identifying Human
Blood Group Based on Image Processing Assisted Deep Learning Principles", 2024 International Conference on Innovative
Computing, Intelligent Communication and Smart Electrical Systems (ICSES), Chennai, India, 2024, pp. 1-6, doi:
10.1109/ICSES63760.2024.1091
6. S. K. Raghuwanshi and P. S. Pandey, "A Numerical Study of Different Metal and Prism Choice in Surface Plasmon Resonance Biosensor
Chip for Human Blood Group Identification", IEEE Transactions on NanoBioscience, vol. 22, no. 2, pp. 292-300, April 2023, doi:
10.1109/TNB.2022.3185806.
7. R. Rahad, M. A. Haque, M. O. Faruque, A. S. M. Mohsin, M. S. Mobassir and R. H. Sagor, "A Novel Plasmonic MIM Sensor Using
Integrated 1 x 2 Demultiplexer for Individual Lab-on-Chip Detection of Human Blood Group and Diabetes Level in the Visible to Near-
Infrared Region", IEEE Sensors Journal, vol. 24, no. 8, pp. 12034-12041, Apr. 15, 2
8. T. Ansari, T. Jamadar, A. Sonde and I. R. Jamkhandikar, "BLOOD SNAP - Blood Group Detection using Image Processing," 2024
IEEE 4th International Conference on ICT in Business Industry & Government (ICTBIG), Indore, India, 2024, pp. 1-4, doi:
10.1109/ICTBIG64922.2024.10911510.
9. D. Trong Luong, D. Duy Anh, T. Xuan Thang, H. Thi Lan Huong, T. Thuy Hanh and D. Minh Khanh, "Detect, Classify and Count
Blood Cells For Leukemia Cells Using YOLOv5," 2022 7th National Scientific Conference on Using New Technology in Green
Buildings (ATiGB), Da Nang, Vietnam, 2022, pp. 156- 160, doi: 10.1109/ATiGB5648
10. G. Ramkumar, A. S. Rao and V. N. Prasad, "Automated blood group detection using deep learning based on microscopic image
analysis," Journal of Biomedical Informatics, vol. 152, pp. 104627, 2024, doi: 10.1016/j.jbi.2024.104627.
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