Center for Identification Technology Research
CITeR researchers at Clarkson University announce the release of the Clarkson Fingerprint Segmentation (CFSEG) model. CFSEG is a slap fingerprint segmentation model based on the Mask-RCNN architecture trained using a combination of adult and juvenile slap fingerprints. The matching results using the Verifinger fingerprint matcher indicate that CFSEG outperforms NIST NFSEG in adults and juvenile slaps.
The model is publicly available on GitHub. You can also try the model in your browser with a pre-configured Colab environment.
Paper: https://lnkd.in/gjpCtDe7
Github: https://lnkd.in/gk6r5-W3
Google Colab: https://lnkd.in/gpHViTzN
The model is publicly available on GitHub. You can also try the model in your browser with a pre-configured Colab environment.
Paper: https://lnkd.in/gjpCtDe7
Github: https://lnkd.in/gk6r5-W3
Google Colab: https://lnkd.in/gpHViTzN
CITeR is releasing the first of a series of biometric educational videos. The CITeR community created the videos to aid in the understanding of biometric technology, its potential uses, and the security in the technology that helps protect a person's biometric information. https://www.youtube.com/channel/UCwSnCVSl4AJQ37iDZ3v3SIw
CITeR PhD candidates Keivan Bahmani & Richard Plesh were part of the team that developed the Clarkson Fingerprint Generator (CFG), capable of generating realistic, high fidelity, 512×512 pixels, full, plain impression fingerprints.
https://arxiv.org/abs/2105.10403
https://arxiv.org/abs/2105.10403
In this work, we utilize progressive growth-based Generative Adversarial Networks (GANs) to develop the Clarkson Fingerprint Generator (CFG). We demonstrate that the CFG is capable of generating realistic, high fidelity, $512\times512$ pixels, full, plain impression fingerprints. Our results suggest...
CITeR is a National Science Foundation (NSF) Industry/University Cooperative Research Center (I/UCRC).
Our mission is to work in partnership with our government and industry stakeholders to advance the state of the art in human identification capabilities through coordinated university research.
