12 datasets found

Tags: Fingerprint

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  • NIST SD27

    The dataset used in the paper is a high-quality fingerprint image dataset (plain and rolled print) and a poor-quality fingerprint image dataset (latent print).

  • S6-L, S6-SM1, S6-SM2, S6-SM3, S7-L, S7-SM4

    A dataset of live and spoof fingerprint images for training and testing generative models.

  • S1-L, S2-L, S2-L-1, S2-L-2, S2-L-2-1, S2-L-2-2, S3-L, S4-L, S5-L

    A dataset of live and spoof fingerprint images for training and testing generative models.

  • CVBL Dataset

    CVBL dataset is a comprehensive biometric dataset consisting of facial videos, fingerprint, and signature of each subject.

  • SOCOFing dataset

    The SOCOFing dataset is used for fingerprint identification and enhancement. It contains 6,000 fingerprints taken from 600 Africans.

  • SFinGe

    SFinGe is a synthetic fingerprint dataset that can generate fingerprints with varying ridge structures and patterns.

  • NIST SD302

    NIST Special Database 302 contains plain, rolled and touch-free impressions captured from various devices.

  • FVC 2002

    Fingerprint enhancement task can be related to image denoising. However, we need to consider the inherent properties of biometric data and that it should be handled differently...

  • LivDet 2015

    LivDet 2015 comprises of 19,431 fingerprint images acquired from four different sensors: CrossMatch L SCAN GUARDIAN, Digital Persona U are U 5160, HiScan-PRO, and GreenBit...

  • LivDet 2013

    LivDet 2013 comprises 16,000 images acquired from four different sensors: Biometrika FX2000, Crossmatch L SCAN GUARDIAN, Italdata ET10, and Swipe, each having approximately...

  • LivDet 2011

    LivDet 2011 comprises 16,000 images obtained using four different sensors: Biometrika FX2000, Digital 4000B, Italdata ET10, and Sagem MSO300, each having 2000 images of fake and...

  • Fingerprint dataset for gender classification

    Fingerprint dataset containing 6000 images of 200 subjects (102 females and 98 males) with 3 images per subject.
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