Detail publikace

Segmentation Procedure for Fingerprint Area Detection in Image Based on Enhanced Gabor Filtering

DOLEŽEL, M. LODROVÁ, D. BUSCH, C. DRAHANSKÝ, M.

Originální název

Segmentation Procedure for Fingerprint Area Detection in Image Based on Enhanced Gabor Filtering

Anglický název

Segmentation Procedure for Fingerprint Area Detection in Image Based on Enhanced Gabor Filtering

Jazyk

en

Originální abstrakt

This paper describes a detailed description of segmentation procedure for fingerprint area detection in a digital fingerprint image. Purpose of this procedure is to extract very precisely the fingerprint area and to separate it from the image background. The precise fingerprint area detection is important not only for vendors of minutiae extraction algorithms but also for semantic conformance testing for finger minutiae data in the newly created international standard. Our segmentation procedure was evaluated for real-world scenario, so the used fingerprints were scanned from real dactyloscopic fingerprint cards. These fingerprints were taken from Ground Truth Database of fingerprints (used subset of GTD originally belongs to NIST SD14 and SD29 databases). Our procedure had to deal with specific problems and properties of these images such as handwritten or printed characters, drawings or specific noise in the background or spread over the fingerprint itself. Our approach was compared with three other methods and yields significantly better results than the best of the benchmarked methods.

Anglický abstrakt

This paper describes a detailed description of segmentation procedure for fingerprint area detection in a digital fingerprint image. Purpose of this procedure is to extract very precisely the fingerprint area and to separate it from the image background. The precise fingerprint area detection is important not only for vendors of minutiae extraction algorithms but also for semantic conformance testing for finger minutiae data in the newly created international standard. Our segmentation procedure was evaluated for real-world scenario, so the used fingerprints were scanned from real dactyloscopic fingerprint cards. These fingerprints were taken from Ground Truth Database of fingerprints (used subset of GTD originally belongs to NIST SD14 and SD29 databases). Our procedure had to deal with specific problems and properties of these images such as handwritten or printed characters, drawings or specific noise in the background or spread over the fingerprint itself. Our approach was compared with three other methods and yields significantly better results than the best of the benchmarked methods.

Dokumenty

BibTex


@article{BUT50888,
  author="Michal {Doležel} and Dana {Lodrová} and Christoph {Busch} and Martin {Drahanský}",
  title="Segmentation Procedure for Fingerprint Area Detection in Image Based on Enhanced Gabor Filtering",
  annote="This paper describes a detailed description of segmentation procedure for
fingerprint area detection in a digital fingerprint image. Purpose of this
procedure is to extract very precisely the fingerprint area and to separate it
from the image background. The precise fingerprint area detection is important
not only for vendors of minutiae extraction algorithms but also for semantic
conformance testing for finger minutiae data in the newly created international
standard.
Our segmentation procedure was evaluated for real-world scenario, so the used
fingerprints were scanned from real dactyloscopic fingerprint cards. These
fingerprints were taken from Ground Truth Database of fingerprints (used subset
of GTD originally belongs to NIST SD14 and SD29 databases). Our procedure had to
deal with specific problems and properties of these images such as handwritten or
printed characters, drawings or specific noise in the background or spread over
the fingerprint itself. Our approach was compared with three other methods and
yields significantly better results than the best of the benchmarked methods.",
  address="NEUVEDEN",
  booktitle="International Journal of Bio-Science and Bio-Technology",
  chapter="50888",
  edition="NEUVEDEN",
  howpublished="print",
  institution="NEUVEDEN",
  number="3",
  volume="2010",
  year="2010",
  month="december",
  pages="39--50",
  publisher="NEUVEDEN",
  type="journal article - other"
}