Titlebook: Handbook of Fingerprint Recognition; Davide Maltoni,Dario Maio,Salil Prabhakar Book 20092nd edition The Editor(s) (if applicable) and The

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Zukunftsf?hige Unternehmensführungints found an application in forensics. By matching leftover fingerprint smudges (latents) from crime scenes to fingerprints collected during booking, authorities could determine the identity of criminals who have been previously arrested. The law enforcement agencies sponsored a rigorous study of f

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https://doi.org/10.1007/978-3-642-17607-4sition techniques, this innovation is undoubtedly more important for a broad range of civil and commercial applications where user acceptance and convenience, low-cost, and reliability are necessary and expected. In civil and commercial applications, certainly, an employee cannot be expected to appl

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https://doi.org/10.1007/978-3-0348-5088-9e extraction and matching algorithms are usually quite similar for both fingerprint verification and identification problems. This is because the fingerprint identification problem (i.e., searching for an input fingerprint in a database of . fingerprints) can be implemented as a sequential execution

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https://doi.org/10.1007/978-3-662-69276-9nt database into a number of bins (based on some predefined classes). A fingerprint to be identified is then required to be compared only to the fingerprints in a single bin of the database based on its class..Fingerprint classification refers to the problem of assigning a fingerprint to a class in

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https://doi.org/10.1007/978-3-658-34253-1d Jain, 2006), and fingerprint systems in particular, is an instance of information fusion (Dasarathy, 1994). A strong theoretical base as well as numerous empirical studies has been documented that support the advantages of fusion in fingerprint systems. The main advantage of fusion in the context

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