Iris Recognition Development Techniques: A Comprehensive Review

Recently, iris recognition techniques have achieved great performance in identification. Among authentication techniques, iris recognition systems have received attention very much due to their rich iris texture which gives robust standards for identifying individuals. Notwithstanding this, there ar...

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Bibliographic Details
Published in:Complexity (New York, N.Y.) N.Y.), 2021, Vol.2021 (1)
Main Authors: Malgheet, Jasem Rahman, Manshor, Noridayu Bt, Affendey, Lilly Suriani
Format: Article
Language:English
Subjects:
Accuracy
Automation
Biometric recognition systems
Biometrics
Deep learning
Eyeglasses
Facial recognition technology
Feature extraction
Feature selection
Identification
Image acquisition
Image classification
Image quality
Image segmentation
Influence
Machine learning
Noise
Object recognition
Physiology
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Summary:Recently, iris recognition techniques have achieved great performance in identification. Among authentication techniques, iris recognition systems have received attention very much due to their rich iris texture which gives robust standards for identifying individuals. Notwithstanding this, there are several challenges in unrestricted recognition environments. In this article, the researchers present the techniques used in different phases of the recognition system of the iris image. The researchers also reviewed the methods associated with each phase. The recognition system is divided into seven phases, namely, the acquisition phase in which the iris images are acquired, the preprocessing phase in which the quality of the iris image is improved, the segmentation phase in which the iris region is separated from the background of the image, the normalization phase in which the segmented iris region is shaped into a rectangle, the feature extraction phase in which the features of the iris region are extracted, the feature selection phase in which the unique features of the iris are selected using feature selection techniques, and finally the classification phase in which the iris images are classified. This article also explains the two approaches of iris recognition which are the traditional approach and the deep learning approach. In addition, the researchers discuss the advantages and disadvantages of previous techniques as well as the limitations and benefits of both the traditional and deep learning approaches of iris recognition. This study can be considered as an initial step towards a large-scale study about iris recognition.
ISSN:1076-2787
1099-0526
DOI:10.1155/2021/6641247