• Aksheen Malhotra
• Chethana. N
• D.R Nagapranitha
• Sanjana Anand
• Shruthi.B

Blood group detection is a vital procedure during conducting any transfusion of blood during critical transplants or emergencies. Currently, blood group determination tests are performed under standard laboratory conditions by experienced technicians. A novel method employing the technique of Image processing is used in this research paper to deduce blood group with less consumption of time and elimination of personnel error. Clear pictures of the blood samples which are tested are taken from the laboratory. These pictures of the blood samples are captured after the addition of commercial antigen reagents, and are processed using image processing techniques such as Preprocessing, Thresholding, Morphological operations, HSL Luminance plane extraction and Quantification. The blood group is determined by looking for agglutination in the sample image on reaction with a specific reagent, and calculating the intensity variations of the pixels. This procedure can find its application as a self-testing device that does not require any technician supervision, thus reducing the clinical exposure of patients, and reducing human-to-human contact which is of utmost significance in situations where these could be further detrimental to the health of the patient like in the ongoing COVID-19 pandemic.

Blood phenotype, Agglutination, Antigen, Image processing, OpenCV, Raspberry Pi, Pandemic

"Automated Blood Group Determination Using Image Processing Techniques With Integration of Raspberry Pi ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.d954-d965, June-2021, Available :http://www.jetir.org/papers/JETIR2106548.pdf

"Automated Blood Group Determination Using Image Processing Techniques With Integration of Raspberry Pi ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppd954-d965, June-2021, Available at : http://www.jetir.org/papers/JETIR2106548.pdf