Employing Image-Based Canny Edge Detection Method for Blood Group Detection

Abstract

                        In emergencies, quickly and accurately determining the blood types is very critical before performing a blood transfusion. So, if the method of testing blood is done effectively at less cost, with the technology available and without the possibility of human error, it will be a very efficient and potentially life-saving approach. In this paper, we propose a blood group detecting system that is fast, accurate, and reliable. The method where the blood sample image is subjected to a series of algorithms like grayscale, binary, and canny edge detection. The detected edges will then be counted, and compared with the dataset to detect the blood group.