A survey on fingerprint minutiae-based local matching for verification and identification: taxonomy and experimental evaluation

Fingerprint recognition has found a reliable application for verification or identification of people in biometrics. Globally, fingerprints can be viewed as valuable traits due to several perceptions observed by the experts; such as the distinctiveness and the permanence on humans and the performanc...

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Detalles Bibliográficos
Autores: Peralta, Daniel, Galar Idoate, Mikel, Triguero, Isaac, Paternain Dallo, Daniel, García, Salvador, Barrenechea Tartas, Edurne, Benítez, José Manuel, Bustince Sola, Humberto, Herrera, Francisco
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2015
País:España
Institución:Universidad Pública de Navarra
Repositorio:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/17645
Acceso en línea:https://hdl.handle.net/2454/17645
Access Level:acceso abierto
Palabra clave:Biometrics
Fingerprint verification
Fingerprint identification
Local matching
Minutiae
Descripción
Sumario:Fingerprint recognition has found a reliable application for verification or identification of people in biometrics. Globally, fingerprints can be viewed as valuable traits due to several perceptions observed by the experts; such as the distinctiveness and the permanence on humans and the performance in real applications. Among the main stages of fingerprint recognition, the automated matching phase has received much attention from the early years up to nowadays. This paper is devoted to review and categorize the vast number of fingerprint matching methods proposed in the specialized literature. In particular, we focus on local minutiae-based matching algorithms, which provide good performance with an excellent trade-off between efficacy and efficiency. We identify the main properties and differences of existing methods. Then, we include an experimental evaluation involving the most representative local minutiae-based matching models in both verification and evaluation tasks. The results obtained will be discussed in detail, supporting the description of future directions.