Blood Type Identification System in Humans Based on Digital Image Processing

Muzaki Muaki; Aeri Rachmad; Indra Indra; Irfan AP

doi:10.55927/fjcis.v5i1.16641

Authors

Muzaki Muaki Universitas Sulawesi Barat
Aeri Rachmad Universitas Trunojoyo
Indra Indra Universitas Sulawesi Barat
Irfan AP Universitas Sulawesi Barat

DOI:

https://doi.org/10.55927/fjcis.v5i1.16641

Keywords:

Blood Type, Artificial Neural Network, Backpropagation

Abstract

Humans strive to imitate expertise through artificial intelligence approaches, including in medical diagnosis such as distinguishing human blood types A, B, AB, and O. Artificial Neural Networks (ANN) have been developed as a generalization of mathematical models of human learning. This paper discusses the development of ANN software to detect human blood types through recognition of clotting patterns. The clotting patterns of the four blood types can be distinguished well by experts. ANN with the backpropagation learning method is applied as expert learning to recognize blood types based on the clotting pattern formed after antigen reagents are administered. Several image pre-processing stages are used, including edge detection and feature extraction, to improve the recognition process and support accurate blood type identification through artificial intelligence techniques.

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