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Blood Group Determination and Classification Using Raspberry Pi3.
- Source :
- AIP Conference Proceedings; 2020, Vol. 2222 Issue 1, p030002-1-030002-8, 8p, 8 Color Photographs, 1 Black and White Photograph, 1 Diagram
- Publication Year :
- 2020
-
Abstract
- Blood grouping is the first and foremost essentiality for many of the major medical procedures. Traditional ways of detecting blood group have remained analogue in this era of digitization and are therefore susceptible to human fallibility. Digital methods are essential in handling blood group identification and classification reduces error. So it would be very efficient and arguably a lifesaving approach if the process of detecting blood can be completed successfully in a cost effective way with the technologies at hand and without the plausibility of man-made error. This proposition is expected to evaluate the Rh factor as well as the group of a sample blood with its computed image. The whole process excludes a major probability of human error while detecting the agglutination from the traditional method and it would get the task done within a fairly insignificant amount of time. The procedure will start by taking a photo of the sample blood slide followed by the application of a number of algorithms such as grey scale, binary and canny edge detection on it. After that, the detected edges will be counted and thus we will decide the agglutination. The method is established upon real-time dataset including 100 blood samples of people of different ages. The experimental result is almost accurate compared to the real time results from the sample dataset. It can, therefore, conclude the procedure with certain numeric values which were determined after realtime data analysis of images from a Camera, to make it simpler and more precise. [ABSTRACT FROM AUTHOR]
- Subjects :
- BLOOD groups
RH factor
ERROR probability
BLOOD sampling
RASPBERRIES
Subjects
Details
- Language :
- English
- ISSN :
- 0094243X
- Volume :
- 2222
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- AIP Conference Proceedings
- Publication Type :
- Conference
- Accession number :
- 142755233
- Full Text :
- https://doi.org/10.1063/5.0003932