Auflistung nach Schlagwort "Retina"
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- KonferenzbeitragApplication of affine-based reconstruction to retinal point patterns(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Sadeghpour, Mahshid; Arakala, Arathi; Davis, Stephen A.; Horadam, Kathy J.Inverse biometrics that exploit the information of biometric references from comparison scores can compromise sensitive personal information of the users in biometric recognition systems. One inverse biometric method that has been very successful in regenerating face images applies an affine transformation to model the face recognition algorithm. This method is general and could apply to templates extracted from other biometric characteristics. This research proposes two formats to apply this method to spatial point patterns extracted from retina images and tests its performance on reconstructing such sparse templates. The results show that the quality of the reconstructed retina point pattern templates is lower than would be accepted by the system as mated.
- KonferenzbeitragIs There Any Similarity Between a Person’s Left and Right Retina?(BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Biswas, Sangeeta; Rohdin, Johan; Mňuk, Tomáš; Drahanský, MartinIt is often argued among biometric researchers that the left and right retinas of the same person are as different as the retinas of two different persons. In this paper we investigate to what extent this is true. We perform experiments where human volunteers are asked to judge whether a pair of the left and right retinal images displayed side-by-side belongs to the same person or two different persons. We also use two similarity measurements, structural similarity (SSIM) and cosine similarity, to do the investigation process automatically. Our experiments show that there is recognizable similarity in the left and right retina of a person. For a verification task done by human volunteers, the average accuracy was 82%. For identification tasks, automatic systems using cosine similarity were correct in up to 57%.