Footprint Data Analysis of Patient for Diabetics Diagnosis

  • C.Lavanya, S.Christy

Abstract

Biometric parameters can be used to gather a small print of the patient's health. Observation of a person's health square measure is typically tired of the various ways in which it is observed. The health of the patient is a square measure typically determined by the image processing technique. The digital image processing square measure typically applied among the different fields, such as medical, geology, analysis, etc., throughout this paper, proposes a footprint technology that could capture the patient's footprint through webcam victimization. The captured image square measure is typically analyzed by the victimization of the shape and thus by the dimension analysis. The footprint can read the identity of everyone. Based on the identity and therefore the numbers, the system of the image processing is enforced. This uses raspberry pi as a result of a limit of 0.5. The information collected by the webcam square measure is normally stored in the South Dakota card. Allocation of information between the memory path is completed. The classification of the information is based on the victimization of the information separation formula. The color analysis will pose itself as an enormous position based on the color that we seem to be able to identify the footprint to make it possible for any study. Their area unit several steps square measure typically occurs by image acquisition, edge detection, object extraction, pattern recognition, pattern matching. The matched image square measure is typically provided as a result of the above analysis. Based on the result, the square measure of the health condition is typically expected. This approach is extremely effective and acceptable compared to the various techniques used.

Published
2020-06-01
How to Cite
C.Lavanya, S.Christy. (2020). Footprint Data Analysis of Patient for Diabetics Diagnosis. International Journal of Advanced Science and Technology, 29(7s), 5060 - 5064. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/25788