Matches in SemOpenAlex for { <https://semopenalex.org/work/W2153075841> ?p ?o ?g. }
Showing items 1 to 77 of
77
with 100 items per page.
- W2153075841 abstract "Schwarz's technique for printing amino acid solutions introduces the possibility of printing large quantities of latent fingerprints for crime scene investigation quality assurance. Nevertheless his technique also unintentionally creates the possibility of leaving printed fingerprints at crime scenes. To help identify those false fingerprints, in our paper we extend the printing pipeline, for training investigators and detection methods. Furthermore, we propose subjective and objective evaluation approaches and first tendencies for boundary ranges for objective evaluation metrics. In particular we use digitized real latent fingerprints as printing source (= template) and different contactless sensors (two different chromatic white light sensors, FRT CWL 600, FRT CWL 1mm, and a confocal microscope Keyence VK-X105) for their acquisition. For the examination of the printed fingerprints one subjective and two objective evaluation approaches are introduced as well as a first tendency for boundary ranges of the objective approach. A Canon PIXMA IP 4600 is used for printing and the Keyence VK-X105 acquires the untreated printed fingerprints. Our benchmarking results show that the acquisition sensor Keyence VK-X105 leads to the highest quality of printed fingerprints. In respect to the boundary ranges our suggested first tendency is: correlation value with 20x-objective: Best = [0,...,0.1150], Average = [0.1151,...,0.1258], Worst = [0.1259,...,1]. With 50x-objective: Best = [0,...,0.1299], Average = [0.1300,..., 0.1443], Worst = [0.1444,...,1]. And for the average value with 20x-objective: Best = [0,...,0.0171], Average = [0.0172,...,0.0260], Worst = [0.0261,...,1]. And with 50x-objective: Best = [0,...,0.0299], Average = [0.0300,...,0.0470], Worst = [0.0471,...,1]." @default.
- W2153075841 created "2016-06-24" @default.
- W2153075841 creator A5033843025 @default.
- W2153075841 creator A5037254587 @default.
- W2153075841 creator A5052442484 @default.
- W2153075841 creator A5059804529 @default.
- W2153075841 date "2013-04-01" @default.
- W2153075841 modified "2023-09-28" @default.
- W2153075841 title "High quality training materials to detect printed fingerprints: Benchmarking three different aquisition sensors producing printing templates" @default.
- W2153075841 cites W2000178901 @default.
- W2153075841 cites W2072988322 @default.
- W2153075841 cites W2076184005 @default.
- W2153075841 cites W2145094724 @default.
- W2153075841 cites W2163084064 @default.
- W2153075841 cites W2005909620 @default.
- W2153075841 doi "https://doi.org/10.1109/iwbf.2013.6547315" @default.
- W2153075841 hasPublicationYear "2013" @default.
- W2153075841 type Work @default.
- W2153075841 sameAs 2153075841 @default.
- W2153075841 citedByCount "1" @default.
- W2153075841 countsByYear W21530758412013 @default.
- W2153075841 crossrefType "proceedings-article" @default.
- W2153075841 hasAuthorship W2153075841A5033843025 @default.
- W2153075841 hasAuthorship W2153075841A5037254587 @default.
- W2153075841 hasAuthorship W2153075841A5052442484 @default.
- W2153075841 hasAuthorship W2153075841A5059804529 @default.
- W2153075841 hasConcept C127413603 @default.
- W2153075841 hasConcept C136229726 @default.
- W2153075841 hasConcept C144133560 @default.
- W2153075841 hasConcept C153180895 @default.
- W2153075841 hasConcept C154945302 @default.
- W2153075841 hasConcept C162853370 @default.
- W2153075841 hasConcept C199360897 @default.
- W2153075841 hasConcept C3019308078 @default.
- W2153075841 hasConcept C31972630 @default.
- W2153075841 hasConcept C41008148 @default.
- W2153075841 hasConcept C43521106 @default.
- W2153075841 hasConcept C86251818 @default.
- W2153075841 hasConceptScore W2153075841C127413603 @default.
- W2153075841 hasConceptScore W2153075841C136229726 @default.
- W2153075841 hasConceptScore W2153075841C144133560 @default.
- W2153075841 hasConceptScore W2153075841C153180895 @default.
- W2153075841 hasConceptScore W2153075841C154945302 @default.
- W2153075841 hasConceptScore W2153075841C162853370 @default.
- W2153075841 hasConceptScore W2153075841C199360897 @default.
- W2153075841 hasConceptScore W2153075841C3019308078 @default.
- W2153075841 hasConceptScore W2153075841C31972630 @default.
- W2153075841 hasConceptScore W2153075841C41008148 @default.
- W2153075841 hasConceptScore W2153075841C43521106 @default.
- W2153075841 hasConceptScore W2153075841C86251818 @default.
- W2153075841 hasLocation W21530758411 @default.
- W2153075841 hasOpenAccess W2153075841 @default.
- W2153075841 hasPrimaryLocation W21530758411 @default.
- W2153075841 hasRelatedWork W185362579 @default.
- W2153075841 hasRelatedWork W2004162080 @default.
- W2153075841 hasRelatedWork W2035741869 @default.
- W2153075841 hasRelatedWork W2167330962 @default.
- W2153075841 hasRelatedWork W2326383905 @default.
- W2153075841 hasRelatedWork W2799251866 @default.
- W2153075841 hasRelatedWork W3015992554 @default.
- W2153075841 hasRelatedWork W2562034834 @default.
- W2153075841 hasRelatedWork W2813904266 @default.
- W2153075841 hasRelatedWork W2823363259 @default.
- W2153075841 hasRelatedWork W2824012152 @default.
- W2153075841 hasRelatedWork W2855022928 @default.
- W2153075841 hasRelatedWork W2858622515 @default.
- W2153075841 hasRelatedWork W2933817475 @default.
- W2153075841 hasRelatedWork W2956438969 @default.
- W2153075841 hasRelatedWork W2962555762 @default.
- W2153075841 hasRelatedWork W2965523124 @default.
- W2153075841 hasRelatedWork W2976341623 @default.
- W2153075841 hasRelatedWork W3001362020 @default.
- W2153075841 hasRelatedWork W3141924258 @default.
- W2153075841 isParatext "false" @default.
- W2153075841 isRetracted "false" @default.
- W2153075841 magId "2153075841" @default.
- W2153075841 workType "article" @default.