Melissa K. Taylor, Nicholas G. Paulter Jr., Qijun Zhao, Yi Zhang, Anil K. Jain
Fingerprint minutiae are the most important features used by latent fingerprint examiners, as well as in automated fingerprint recognition systems. Hence, understanding the statistical distribution of minutiae is essential in many fingerprint recognition related problems, such as fingerprint individually and fingerprint synthesis. Prior work considers the occurrence of a minutia as a random event, and mostly assumes that individual minutiae are independent of each other. Some studies also considered the clustering tendency of minutiae and the minutiae investigates the correlation between ridge orientation field and minutiae. [full 1,400+ character abstract cannot fit in this space; please see the document for full abstract]
, Paulter, N.
, Zhao, Q.
, Zhang, Y.
and Jain, A.
A Generative Model for Fingerprint Minutiae, Other, National Institute of Standards and Technology, Gaithersburg, MD, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=913906
(Accessed December 2, 2023)