Published Paper Details:

An Iris biometrics has gained a lot of attention as of late. It happened because this quantifiable trait ensures a high level of efficiency and accuracy. Recently, iris recognition algorithms have shown outstanding identifying performance. There has been a rise in the use of iris recognition systems as an authentication method due to the fact that an individual's iris is a perfect biometric candidate due to its rich texture. This article details the methods used by the researchers at various points of the iris image recognition system. Additionally, the procedures linked to each stage were examined by the researchers. Seven phases comprise the recognition system: iris image acquisition; iris image quality improvement during the preprocessing phase; segmentation phase involving the separation of an iris region by an image background; normalisation phase involving a rectangle shaping of a segmented iris region; feature extraction phase encompassing an extraction of iris region features; and finalisation phase encompassing feature extraction. The comparative results have shown the Convolutional Neural Network (CNN) with Gaussian filter (GF) model obtained 99.99% accuracy that is higher than other models. This research endeavours to examine and delineate the phases of existing iris recognition systems.