On the Feasibility of Creating Iris Periocular Morphed Images
This work addresses security vulnerabilities in biometric systems, specifically for iris recognition, by exploring morphing attacks, but it is incremental as it extends face morphing techniques to another modality.
The paper tackled the problem of creating realistic iris periocular morphed images to test biometric system vulnerabilities, resulting in an end-to-end framework that produces images capable of confusing conventional iris recognition systems.
In the last few years, face morphing has been shown to be a complex challenge for Face Recognition Systems (FRS). Thus, the evaluation of other biometric modalities such as fingerprint, iris, and others must be explored and evaluated to enhance biometric systems. This work proposes an end-to-end framework to produce iris morphs at the image level, creating morphs from Periocular iris images. This framework considers different stages such as pair subject selection, segmentation, morph creation, and a new iris recognition system. In order to create realistic morphed images, two approaches for subject selection are explored: random selection and similar radius size selection. A vulnerability analysis and a Single Morphing Attack Detection algorithm were also explored. The results show that this approach obtained very realistic images that can confuse conventional iris recognition systems.