Digital Image Processing Based Blood Group Analysis in Healthcare Application for Humans

S. Karthikeyan*
*UG Scholar, Department of Electrical and Electronics Engineering, AVS Engineering College, Salem, Tamil Nadu, India..
Periodicity:April - June'2018
DOI : https://doi.org/10.26634/jip.5.2.15015

Abstract

The primary objective of this work is image processing based blood groups identification that utilizes the digital image matching process without using needles. Now-a-days, the blood group testing uses needles and also utilizes some chemicals, optical plates, cotton cloths, etc. Above biomaterial disposal in the environment is very dangerous and also creates environmental soil pollution. Non-bio degradable materials are the main pollution sources in soil. Technology and various researches have dominated to save human blood and to control the soil pollution and thus the present situation is met. The novel blood group testing is done by finding blood group of a patient without piercing the skin. This article explains a method to determine the human blood type by applying digital image processing to understand the image of artificial vessels underlying the skin. The research includes Multicore wavelength light sprinkling method, where light passes through the vessels for classifying the blood cells based on exact antigens on the red blood cell surface. The transferrable camera along with photo-detectors forms the basic detector structure and is used to detect the light distribution produced by blood cell to determine the blood type. This research presents a current state-of-the-art in optimizing digital image processing based blood group identification, which provides a clear vision of the latest top research advances in image processing with the help of MatLab and Embedded C program.

Keywords

Red Blood Cell, Embedded C, Optical, Photo Detector, Antigen.

How to Cite this Article?

Karthikeyan,S.(2018). Digital Image Processing Based Blood Group Analysis in Healthcare Application for Humans. i-manager’s Journal on Image Processing , 5(2),18-22. https://doi.org/10.26634/jip.5.2.15015

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