Adaptive Fingerprint Image Enhancement with Emphasis on Preprocessing of Data
(2013) In IEEE Transactions on Image Processing 22(2). p.644-656- Abstract
- This article proposes several improvements to an
adaptive fingerprint enhancement method that is based on
contextual filtering. The term adaptive implies that parameters
of the method are automatically adjusted based on the input
fingerprint image. Five processing blocks comprise the adaptive
fingerprint enhancement method, where four of these blocks are
updated in our proposed system. Hence, the proposed overall
system is novel. The four updated processing blocks are; preprocessing,
global analysis, local analysis and matched filtering.
In the pre-processing and local analysis blocks, a nonlinear
dynamic range adjustment method is used. In the global... (More) - This article proposes several improvements to an
adaptive fingerprint enhancement method that is based on
contextual filtering. The term adaptive implies that parameters
of the method are automatically adjusted based on the input
fingerprint image. Five processing blocks comprise the adaptive
fingerprint enhancement method, where four of these blocks are
updated in our proposed system. Hence, the proposed overall
system is novel. The four updated processing blocks are; preprocessing,
global analysis, local analysis and matched filtering.
In the pre-processing and local analysis blocks, a nonlinear
dynamic range adjustment method is used. In the global analysis
and matched filtering blocks, different forms of order statistical
filters are applied. These processing blocks yield an improved
and new adaptive fingerprint image processing method. The
performance of the updated processing blocks is presented in the
evaluation part of this paper. The algorithm is evaluated towards
the NIST developed NBIS software for fingerprint recognition on
FVC databases. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3294696
- author
- Ström Bartunek, Josef ; Nilsson, Mikael LU ; Sällberg, Benny and Claesson, Ingvar
- organization
- publishing date
- 2013
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- successive mean quantization transform, Fourier transform, image processing, directional filtering, spectral feature estimation
- in
- IEEE Transactions on Image Processing
- volume
- 22
- issue
- 2
- pages
- 644 - 656
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- wos:000314717800019
- scopus:84872237660
- pmid:23014753
- ISSN
- 1941-0042
- DOI
- 10.1109/TIP.2012.2220373
- language
- English
- LU publication?
- yes
- id
- 44d2238c-b59f-4756-8264-e4baa1caf856 (old id 3294696)
- date added to LUP
- 2016-04-01 10:40:02
- date last changed
- 2022-01-26 01:18:57
@article{44d2238c-b59f-4756-8264-e4baa1caf856,
abstract = {{This article proposes several improvements to an<br/><br>
adaptive fingerprint enhancement method that is based on<br/><br>
contextual filtering. The term adaptive implies that parameters<br/><br>
of the method are automatically adjusted based on the input<br/><br>
fingerprint image. Five processing blocks comprise the adaptive<br/><br>
fingerprint enhancement method, where four of these blocks are<br/><br>
updated in our proposed system. Hence, the proposed overall<br/><br>
system is novel. The four updated processing blocks are; preprocessing,<br/><br>
global analysis, local analysis and matched filtering.<br/><br>
In the pre-processing and local analysis blocks, a nonlinear<br/><br>
dynamic range adjustment method is used. In the global analysis<br/><br>
and matched filtering blocks, different forms of order statistical<br/><br>
filters are applied. These processing blocks yield an improved<br/><br>
and new adaptive fingerprint image processing method. The<br/><br>
performance of the updated processing blocks is presented in the<br/><br>
evaluation part of this paper. The algorithm is evaluated towards<br/><br>
the NIST developed NBIS software for fingerprint recognition on<br/><br>
FVC databases.}},
author = {{Ström Bartunek, Josef and Nilsson, Mikael and Sällberg, Benny and Claesson, Ingvar}},
issn = {{1941-0042}},
keywords = {{successive mean quantization transform; Fourier transform; image processing; directional filtering; spectral feature estimation}},
language = {{eng}},
number = {{2}},
pages = {{644--656}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Image Processing}},
title = {{Adaptive Fingerprint Image Enhancement with Emphasis on Preprocessing of Data}},
url = {{http://dx.doi.org/10.1109/TIP.2012.2220373}},
doi = {{10.1109/TIP.2012.2220373}},
volume = {{22}},
year = {{2013}},
}