An Enhancement of the Usage of the Poincare Index for the Detection and Classification of Characteristic Points in Dactylograms

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dc.contributor.authorAngélica González Arrieta
dc.contributor.authorMarco A. Ameller F.
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T20:23:44Z
dc.date.available2026-03-22T20:23:44Z
dc.date.issued2011
dc.identifier.doi10.1007/978-3-642-19914-1_17
dc.identifier.urihttps://doi.org/10.1007/978-3-642-19914-1_17
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/81738
dc.language.isoen
dc.publisherSpringer Science+Business Media
dc.relation.ispartofAdvances in intelligent and soft computing
dc.sourceUniversidad de Salamanca
dc.subjectBiometrics
dc.subjectArtificial intelligence
dc.subjectComputer science
dc.subjectPattern recognition (psychology)
dc.subjectFingerprint (computing)
dc.subjectFace (sociological concept)
dc.subjectIdentification (biology)
dc.subjectSet (abstract data type)
dc.subjectComputer vision
dc.subjectFeature (linguistics)
dc.titleAn Enhancement of the Usage of the Poincare Index for the Detection and Classification of Characteristic Points in Dactylograms
dc.typebook-chapter

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