Sclera Segmentation on the Half-UNet Neural Network

Nowadays, technology for biometric authentication technologies is actively implemented, users can usually authenticate themselves by their face, voice, fingerprint, vascular bed of the finger, palm, iris. Using images of sclera vessels for authentication is mathematically and technically more complex, so it is used less often. In addition, existing sclera segmentation algorithms often do not allow ensuring the required quality of authentication systems. The paper proposes an algorithm for sclera segmentation based on the lightweight convolutional neural network Half-UNet, and compares the obtained results with known algorithms for sclera segmentation. Analysis of the obtained results shows that the developed algorithm effectively highlights the eye sclera region, surpassing known modern algorithms, and can be used in implementation of biometric authentication system as a stage of processing scanner images before the sclera vessels segmentation stage.