On the Feasibility of Creating Iris Periocular Morphed Images
원문 초록
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.
함께 살펴볼 논문
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LADIMO: Face Morph Generation through Biometric Template Inversion with Latent Diffusion
MorphGuard: Morph Specific Margin Loss for Enhancing Robustness to Face Morphing Attacks
ChatGPT Encounters Morphing Attack Detection: Zero-Shot MAD with Multi-Modal Large Language Models and General Vision Models
Facial Demorphing via Identity Preserving Image Decomposition
ChatGPT Meets Iris Biometrics
Attributes Shape the Embedding Space of Face Recognition Models
토론
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