Restore FingerPrint.

FingerPrint Processing.

This model allows you to detect if spoof finger-print verification and restore incomplete images of fingerprint.

With this lab based at deep learning-based models have been shown improve the accuracy of fingerprint recognition. That using convolutional neural networks (CNNs) can push the limits of fingerprint recognition, achieving state-of-the-art performance. However, the dataset has strong privacy requieremet, these algorithms require large-scale fingerprint datasets for training and evaluation, and used fragmented finger image was significat. To address this issue, this lab propose a novel fingerprint synthesis and reconstruction framework based on the StyleGan2 architecture with the generation of realistic synthetic fingerprint images while preserving the identity of the original fingerprints. News changes was introduced approach to modify the attributes of the generated fingerprints, such as rotation, translation, and scaling, without altering their identity. This enables the synthesis of multiple different fingerprint images per finger, effectively increasing the size of the training dataset. Deploy new system for identify and determinate the terms of their ability to detect spoof fingerprint-based verification systems. This lab propouse new tools that help Govermnet Departaments for identify, restore and make trazability of any fingerprint.