MiDeCon: Unsupervised and Accurate Fingerprint and Minutia Quality Assessment based on Minutia Detection Confidence

Terhörst, Philipp; Boller, André; Damer, Naser; Kirchbuchner, Florian; Kuijper, Arjan

doi:10.1109/ijcb52358.2021.9484404

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Fig 16 Category Of Fingerprints Available In Dataset1

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2022

2024

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Cited by 7 publications

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“…The minutiae points can be classified into six classes viz. ending, bifurcation, fragment, enclosure, crossbar and others [24] [25]. Table IV shows a few samples of such different classes that have been detected from the family fingerprint dataset.…”

Section: Fig 16 Category Of Fingerprints Available In Datasetmentioning

confidence: 99%

Quality and Feature Analysis of Parent and Child Fingerprints in West Bengal, India

Maiti,

Basak,

Das

2023

IJRASET

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Fingerprint image of father, mother and child in ink paper method are collected from the region of West Bengal, India. One Hundred family without having kinship relation are involved in the data collection process. The paper is scanned with a HP scanner with 1200 ppi resolution and pre-processed with different technique to form a dataset of 1500 fingerprint images. Different non reference and reference image quality assessment technique are applied to test the quality of the image dataset. Minutiae based feature are extracted from the images to find a correlation between child and parent’s fingerprints. This family fingerprint dataset can be used by the researchers to find an alternative of DNA matching for parental verification or other research works.

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Section: Fig 16 Category Of Fingerprints Available In Datasetmentioning

confidence: 99%