LEADER 04065nam 22005535 450 001 9910349270803321 005 20200702161945.0 010 $a3-030-23364-2 024 7 $a10.1007/978-3-030-23364-8 035 $a(CKB)4100000009606259 035 $a(MiAaPQ)EBC5967894 035 $a(DE-He213)978-3-030-23364-8 035 $a(PPN)258861460 035 $a(EXLCZ)994100000009606259 100 $a20191022d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSegmentation and Separation of Overlapped Latent Fingerprints $eAlgorithms, Techniques, and Datasets /$fby Branka Stojanovi?, Oge Marques, Aleksandar Ne?kovi? 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (61 pages) 225 1 $aSpringerBriefs in Computer Science,$x2191-5768 311 $a3-030-23363-4 327 $a1 Latent fingerprint matching systems -- 2 Latent fingerprint datasets -- 3 Overlapped latent fingerprints segmentation: problem definition -- 4 Machine learning based segmentation of overlapped latent fingerprints -- 5 Overlapped latent fingerprints separation: problem definition -- 6 Machine learning based separation of overlapped latent fingerprints. 330 $aThis Springerbrief presents an overview of problems and technologies behind segmentation and separation of overlapped latent fingerprints, which are two fundamental steps in the context of fingerprint matching systems. It addresses five main aspects: (1) the need for overlapped latent fingerprint segmentation and separation in the context of fingerprint verification systems; (2) the different datasets available for research on overlapped latent fingerprints; (3) selected algorithms and techniques for segmentation of overlapped latent fingerprints; (4) selected algorithms and techniques for separation of overlapped latent fingerprints; and (5) the use of deep learning techniques for segmentation and separation of overlapped latent fingerprints. By offering a structured overview of the most important approaches currently available, putting them in perspective, and suggesting numerous resources for further exploration, this book gives its readers a clear path for learning new topics and engaging in related research. Written from a technical perspective, and yet using language and terminology accessible to non-experts, it describes the technologies, introduces relevant datasets, highlights the most important research results in each area, and outlines the most challenging open research questions. This Springerbrief targets researchers, professionals and advanced-level students studying and working in computer science, who are interested in the field of fingerprint matching and biometrics. Readers who want to deepen their understanding of specific topics will find more than one hundred references to additional sources of related information. 410 0$aSpringerBriefs in Computer Science,$x2191-5768 606 $aBiometrics (Biology) 606 $aArtificial intelligence 606 $aBiometrics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22040 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 615 0$aBiometrics (Biology). 615 0$aArtificial intelligence. 615 14$aBiometrics. 615 24$aArtificial Intelligence. 676 $a006.3 676 $a006.4 700 $aStojanovi?$b Branka$4aut$4http://id.loc.gov/vocabulary/relators/aut$01063911 702 $aMarques$b Oge$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aNe?kovi?$b Aleksandar$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910349270803321 996 $aSegmentation and Separation of Overlapped Latent Fingerprints$92535253 997 $aUNINA