@inbook{b2a7072d792f44c5bd4cf24925bd3327,
title = "Robust reference point detection using gradient of fingerprint direction and feature extraction method",
abstract = "A novel reference point detection method is proposed by exploiting the GPM(Gradient Probabilistic Model) that captures the curvature information of fingerprint texture. The detection of reference point is accomplished through searching and locating the points of occurrence of the most evenly distributed gradient in probabilistic sense. We also propose a novel filterbank method to improve shortcoming of existing filterbank method in verification part. Existing filterbank method can lose the discerning attributes because the sectors of the outer band from the reference point are larger in size than those of the inner bands. Such shortcomings of the filterbank method are resolved by maintaining the attribute regions to equal size.",
author = "Junbum Park and Hanseok Ko",
note = "Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2003",
doi = "10.1007/3-540-44864-0_113",
language = "English",
isbn = "3540401970",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1089--1099",
editor = "Sloot, {Peter M. A.} and David Abramson and Bogdanov, {Alexander V.} and Gorbachev, {Yuriy E.} and Dongarra, {Jack J.} and Zomaya, {Albert Y.}",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}