Retracted: Discovering Informative Regions in Iris Images to Predict Diabetes

Retracted: A Review of Iris Recognition System ROI and Accuracy

“…In this paper, they use Gray Level Co-Occurrence Matrix (GLCM) feature extraction and Bayesian regularization (BR) classification to diagnose either the subject is suffering from the disease or not. Arcus Senilis [13], [22][23][24][25][26][27] Autonomic Nerve [28] Brain [29] Heart [12], [16], [30][31] Kidney [32] Liver [33] Lung [4], [15], [34] Pancreas [3], [7], [8], [14], [35][36][37] Stomach [38] Iris Recognition System ROI and Accuracy…”

“…Iridologists examine the iris fiber, color, brightness, and shadings by looking at the iris and claim that iridology can predict the risk of disease because signs that represent body debility will appear in iris earlier than the organ itself. [3]. In iridology, there is a chart that can be used to find the organ that the iris represents namely the iridology chart (Fig.…”

“…Based on the observation, they will specify which part of the body is weak or susceptible to suffer from diseases sooner than actual symptoms [4]. Typically, iridology charts divide an iris image into 80 to 90 regions [3]. The iris recognition system usually only analyze one region of the iris.…”