Main Catalog Informatics, Computer Engineering and Control Information Technology. Computer techologies. Theory of computers and systems

Synthesizing iris images using generative adversarial networks

Authors: Konnova N.S., Martynov S.M.
Published in issue: #5(100)/2025
DOI:
Category: Informatics, Computer Engineering and Control \| Chapter: Information Technology. Computer techologies. Theory of computers and systems
Keywords: generative adversarial network (gan), synthetic irides, deep learning, presentation attack, iris recognition
Published: 17.10.2025

Biometric systems based on iris recognition are currently used in various applications: border control, mobile devices, etc. However, research in the field of iris recognition is limited by various factors, such as relatively small sets of bonafide iris images, problems with tools for modeling potential spoofing attacks, and problems with preserving recipients' privacy. Some of these problems can be addressed by using synthetic iris images. This paper provides an overview of state-of-the-art GAN-based synthetic iris image generation methods, analyzing their strengths and limitations in generating realistic iris images that can be used for both training and testing iris recognition systems and spoofing attack detectors. In this regard, we will first review the various methods that are used for synthetic iris generation, in particular, we will consider generators based on StyleGAN, RaSGAN, CIT-GAN, iWarpGAN, StarGAN, etc. We will then analyze the images generated by these models for realism, uniqueness, and biometric usefulness.

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