Gottschlich, Carsten

[["dc.bibliographiccitation.firstpage","802"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","IEEE Transactions on Information Forensics and Security"],["dc.bibliographiccitation.lastpage","811"],["dc.bibliographiccitation.volume","4"],["dc.contributor.author","Gottschlich, Carsten"],["dc.contributor.author","Mihailescu, Preda"],["dc.contributor.author","Munk, Axel"],["dc.date.accessioned","2017-09-07T11:46:45Z"],["dc.date.available","2017-09-07T11:46:45Z"],["dc.date.issued","2009"],["dc.description.abstract","Orientation field ( OF) estimation is a crucial preprocessing step in fingerprint image processing. In this paper, we present a novel method for OF estimation that uses traced ridge and valley lines. This approach provides robustness against disturbances caused, e. g., by scars, contamination, moisture, or dryness of the finger. It considers pieces of flow information from a larger region and makes good use of fingerprint inherent properties like continuity of ridge flow perpendicular to the flow. The performance of the line-sensor method is compared with the gradients-based method and a multiscale directional operator. Its robustness is tested in experiments with simulated scar noise which is drawn on top of good quality fingerprint images from the FVC2000 and FVC2002 databases. Finally, the effectiveness of the line-sensor-based approach is demonstrated on 60 naturally poor quality fingerprint images from the FVC2004 database. All orientations marked by a human expert are made available at the journal's and the authors' website for comparative tests."],["dc.identifier.doi","10.1109/TIFS.2009.2033219"],["dc.identifier.gro","3143017"],["dc.identifier.isi","000271968200005"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/485"],["dc.notes.intern","WoS Import 2017-03-10 / Funder: DFG [FOR 916]; Volkswagen Foundation"],["dc.notes.status","final"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Ieee-inst Electrical Electronics Engineers Inc"],["dc.relation.issn","1556-6013"],["dc.title","Robust Orientation Field Estimation and Extrapolation Using Semilocal Line Sensors"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","11"],["dc.bibliographiccitation.lastpage","20"],["dc.contributor.author","Hotz, Thomas"],["dc.contributor.author","Gottschlich, Carsten"],["dc.contributor.author","Lorenz, Robert"],["dc.contributor.author","Bernhardt, Stefanie"],["dc.contributor.author","Hantschel, Michael"],["dc.contributor.author","Munk, Axel"],["dc.contributor.editor","Brömme, Arslan"],["dc.contributor.editor","Busch, Christoph"],["dc.date.accessioned","2018-02-05T09:43:18Z"],["dc.date.available","2018-02-05T09:43:18Z"],["dc.date.issued","2011"],["dc.description.abstract","We study the effect of growth on the fingerprints of adolescents, based on which we suggest a simple method to adjust for growth when trying to retrieve an adolescent's fingerprint in a database years later. Here, we focus on the statistical analyses used to determine how fingerprints grow: Procrustes analysis allows us to establish that fingerprints grow isotropically, an appropriate mixed effects model shows that fingerprints essentially grow proportionally to body height. The resulting growth model is validated by showing that it brings points of interest as close as if both fingerprints were taken from an adult. Further details on this study, in particular results when applying our growth model in verification and identification tests, can be found in C. Gottschlich, T. Hotz, R. Lorenz, S. Bernhardt, M. Hantschel and A. Munk: Modeling the Growth of Fingerprints Improves Matching for Adolescents, IEEE Transations on Information Forensics and Security, 2011"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/11949"],["dc.language.iso","en"],["dc.notes.status","fcwi-famis"],["dc.publisher","Gesellschaft für Informatik"],["dc.publisher.place","Bonn"],["dc.relation.eventend","09.09.2011"],["dc.relation.eventlocation","Darmstadt"],["dc.relation.eventstart","08.09.2011"],["dc.relation.ispartof","BIOSIG 2011 Proceedings - international conference of the biometrics special interest group"],["dc.title","Statistical analyses of fingerprint growth"],["dc.type","conference_paper"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","529"],["dc.bibliographiccitation.lastpage","533"],["dc.contributor.author","Gottschlich, Carsten"],["dc.contributor.author","Munk, Axel"],["dc.contributor.author","Mihailescu, Preda"],["dc.contributor.editor","Zinterhof, Peter"],["dc.date.accessioned","2017-09-07T11:53:17Z"],["dc.date.available","2017-09-07T11:53:17Z"],["dc.date.issued","2009"],["dc.description.abstract","A good and reliable orientation field (OF) estimation is of great importance in fingerprint image processing. This paper presents an OF estimation approach that is based on traced ridge and furrow lines. The method considers pieces of flow information from a larger region and provides robustness against disturbances caused, e.g. by temporary scars, creases, contamination, wetness or dryness of the finger. The performance of the method is evaluated in simulation runs with artificial ridge interruptions and compared to the gradients based method and a multiscale directional operator."],["dc.identifier.doi","10.1109/ispa.2009.5297684"],["dc.identifier.gro","3145067"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/2762"],["dc.language.iso","en"],["dc.notes.intern","Crossref Import"],["dc.notes.status","final"],["dc.publisher","IEEE"],["dc.publisher.place","Piscataway"],["dc.relation.eventend","2009-09-18"],["dc.relation.eventlocation","Salzburg"],["dc.relation.eventstart","2009-09-16"],["dc.relation.isbn","978-953-184-135-1"],["dc.relation.ispartof","Proceedings of the 6th International Symposium on Image and Signal Processing and Analysis, 2009 : ISPA 2009"],["dc.title","Robust orientation field estimation in fingerprint images with broken ridge lines"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1165"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","IEEE Transactions on Information Forensics and Security"],["dc.bibliographiccitation.lastpage","1169"],["dc.bibliographiccitation.volume","6"],["dc.contributor.author","Gottschlich, Carsten"],["dc.contributor.author","Hotz, Thomas"],["dc.contributor.author","Lorenz, Robert"],["dc.contributor.author","Bernhardt, Stefanie"],["dc.contributor.author","Hantschel, Michael"],["dc.contributor.author","Munk, Axel"],["dc.date.accessioned","2017-09-07T11:43:25Z"],["dc.date.available","2017-09-07T11:43:25Z"],["dc.date.issued","2011"],["dc.description.abstract","We study the effect of growth on the fingerprints of adolescents, based on which we suggest a simple method to adjust for growth when trying to recover a juvenile's fingerprint in a database years later. Based on longitudinal data sets in juveniles' criminal records, we show that growth essentially leads to an isotropic rescaling, so that we can use the strong correlation between growth in stature and limbs to model the growth of fingerprints proportional to stature growth as documented in growth charts. The proposed rescaling leads to a 72% reduction of the distances between corresponding minutiae for the data set analyzed. These findings were corroborated by several verification tests. In an identification test on a database containing 3.25 million right index fingers at the Federal Criminal Police Office of Germany, the number of identification errors was reduced from 10 errors in 48 identification attempts to 1 in 48 by rescaling. The presented method is of striking simplicity and can easily be integrated into existing automated fingerprint identification systems."],["dc.identifier.doi","10.1109/TIFS.2011.2143406"],["dc.identifier.gro","3142678"],["dc.identifier.isi","000293924700026"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/108"],["dc.language.iso","en"],["dc.notes.intern","WoS Import 2017-03-10 / Funder: DFG [RTG 1023, CRC 803]"],["dc.notes.status","final"],["dc.notes.submitter","PUB_WoS_Import"],["dc.relation.issn","1556-6013"],["dc.title","Modeling the Growth of Fingerprints Improves Matching for Adolescents"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original"],["dspace.entity.type","Publication"]]