Why is this so? Indeed, iris patterns are very stable, very unique and last over time, even shortly (a few weeks) after death. So why we cannot do it like before two years of age? In order to investigate a hypothesis that iris recognition is viable for infants, Rasel and team collected data from babies aged 4-12 weeks and designed a custom 4-megapixel CMOS image sensor operating in near infrared, which they used to capture all the data. However, application of stateof-the-art iris recognition models (designed originally for adults) did not provide an accurate identification method. “We saw that infant iris has a brighter pupil than regular iris,” reveals Rasel. “They also have a slightly larger pupil size, and due to that, existing iris image processing methods cannot segment infant iris images accurately.” But can you teach them maybe? Rasel decided to do infant-specific pre-processing and build a segmentation model, which is also infant-specific. To do that, he used iris images collected from adults and then performed infant-specific augmentations, like adjusting the pupil brightness and size, and then he trained the model on such preprocessed data. The resulting model can accurately segment not only infant iris images, but also detects other deformations in iris images and can be applied to, for instance, segmentation of images captured post-mortem or from diseased eyes. The architecture of the model was like a nested U-Net with dilated convolution layers and attention mechanism. Is the model so accurate that you could claim that a child has been swapped, with all the radical consequences upon this child’s life? “This model actually did what we designed it for,” declares Rasel. “With this model you can identify the baby so that you can prevent the swapping!” The method, as any other iris recognition algorithm, can recognize identical twins, and can assist hospital staff in rapid and accurate 15 Computer Vision News Computer Vision News Iris Recognition for Infants
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