Automatic ABO Blood Group Classification Based On Image Processing Techniques

In emergency situations, before transfusion or donation, classifying blood group in a short time plays a vital role in saving human lives. Traditionally, this is done by human technicians, which involves the risk of human errors as well as sluggishness inthe process. For these reasons, this paper presents a methodology using image processing techniques, including thresholding and morphological operations, to classify blood groups based on ABO & Rh blood typing system. The program developed in this project can be easily implemented in computational devices, i.e., Arduino, Teensy 4, etc., in order to develop a faster blood group detection system with precision and accuracy. Apart from its scope to build an automated system, it will be useful in saving precious time in determining blood group precisely, thus saving people's lives if there is no skilled person around in distant places

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-14
DOI
https://doi.org/10.5281/zenodo.18497164
Primary Topic
Blood groups and transfusion
Type
article
Field-Weighted Citation Impact
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article

Automatic ABO Blood Group Classification Based On Image Processing Techniques

Md Tanvir Mahmud Prince
Zenodo (CERN European Organization for Nuclear Research)
Blood groups and transfusion
article

Automatic ABO Blood Group Classification Based On Image Processing Techniques

Md Tanvir Mahmud Prince
article en

Abstract

In emergency situations, before transfusion or donation, classifying blood group in a short time plays a vital role in saving human lives. Traditionally, this is done by human technicians, which involves the risk of human errors as well as sluggishness inthe process. For these reasons, this paper presents a methodology using image processing techniques, including thresholding and morphological operations, to classify blood groups based on ABO & Rh blood typing system. The program developed in this project can be easily implemented in computational devices, i.e., Arduino, Teensy 4, etc., in order to develop a faster blood group detection system with precision and accuracy. Apart from its scope to build an automated system, it will be useful in saving precious time in determining blood group precisely, thus saving people's lives if there is no skilled person around in distant places

Zenodo (CERN European Organization for Nuclear Research)
Bangladesh University of Engineering and Technology (BD)
Openalex Percentile: Top 21%
Blood groups and transfusion
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