Iris recognition method based on segmentation

Keywords: Biometric Recognition System, Iris, Segmentation Technique, Hough transform, Dataset, accuracy

Abstract

The development of science and studies has led to the creation of many modern means and technologies that focused and directed their interests on enhancing security due to the increased need for high degrees of security and protection for individuals and societies. Hence identification using a person's vital characteristics is an important privacy topic for governments, businesses and individuals. A lot of biometric features such as fingerprint, facial measurements, acid, palm, gait, fingernails and iris have been studied and used among all the biometrics, in particular, the iris gets the attention because it has unique advantages as the iris pattern is unique and does not change over time, providing the required accuracy and stability in verification systems. This feature is impossible to modify without risk. When identifying with the iris of the eye, the discrimination system only needs to compare the data of the characteristics of the iris of the person to be tested to determine the individual's identity, so the iris is extracted only from the images taken. Determining correct iris segmentation methods is the most important stage in the verification system, including determining the limbic boundaries of the iris and pupil, whether there is an effect of eyelids and shadows, and not exaggerating centralization that reduces the effectiveness of the iris recognition system. There are many techniques for subtracting the iris from the captured image. This paper presents the architecture of biometric systems that use iris to distinguish people and a recent survey of iris segmentation methods used in recent research, discusses methods and algorithms used for this purpose, presents datasets and the accuracy of each method, and compares the performance of each method used in previous studies

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Author Biographies

Ans Ibrahim Mahameed, University of Al-Hamdaniya

Department of Computer Science

Mohammed Kassim Ahmed, University of Al-Hamdaniya

Master of Communication and Networking Engineering

Department of Computer Science

Noor Basim Abdullah, University of Al-Hamdaniya

Master of Systems Software

Department of Computer Science

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Published
2022-03-31
How to Cite
Mahameed, A. I., Ahmed, M. K., & Abdullah, N. B. (2022). Iris recognition method based on segmentation. EUREKA: Physics and Engineering, (2), 166-176. https://doi.org/10.21303/2461-4262.2022.002341
Section
Computer Science