CARDIOVASCULAR ABNORMALITIES DETECTION THROUGH IRIS USING THRESHOLDING ALGORITHM
Cardiovascular diseases have proven to be the leading reason of death worldwide. To identify cardiovascular diseases at an early stage, often very expensive pathological tests are required. A less costly alternative method for determining the conditions of the organs is highly appreciated, and Iridology is one such popular method. Many researchers have proposed cardiovascular disease identification systems by combining Iridology with computation system. In this study, a novel model for detecting heart abnormalities using Iridology is proposed.
The entire process includes several stages such as target capture, pre-processing, autocropping based on histogram analysis, heart area extraction, and classification using a thresholding algorithm.
The cropping method and classification process are both affected by the iris photography procedure. The iridology expert at Clinic in Indonesia labelled the data as abnormal and normal. The precision produced by the system ranges from 80-83%. Some errors occur due to ineffective cropping. The failed outcome may affect the segmentation process resulting in erroneous segmentation in the heart area eventually.
NILAM UPASANI, ASMITA MANNA, SHATABDI PINGALE, YASHASHREE SHINDE, SAKSHI RATHI, SONALI SURPATNE
Journal of Theoretical and Applied Information Technology, 28th February 2023. Vol.101. No 4
Download full abstract: https://iridology-research.com/pdf/13Vol101No4.pdf