Data di Pubblicazione:
2016
Citazione:
Computational intelligence for biometric applications : a survey / R. Donida Labati, A. Genovese, E. Munoz Ballester, V. Piuri, F. Scotti, G. Sforza. - In: COMPUTING INTERNATIONAL SCIENTIFIC JOURNAL. - ISSN 1727-6209. - 15:1(2016), pp. 40-49.
Abstract:
Biometric systems consist of devices, procedures, and algorithms used to recognize people based on their physiological or behavioral features, known as biometric traits. Computational intelligence (CI) approaches are widely adopted in establishing identity based on biometrics and also to overcome non-idealities typically present in the samples. Typical areas include sample enhancement, feature extraction, classification, indexing, fusion, normalization, and anti-spoofing. In this context, computational intelligence plays an important role in performing of complex non linear computations by creating models from the training data. These approaches are based on supervised as well as unsupervised training techniques. This work presents computational intelligence techniques applied to biometrics, from both a theoretical and an application point of view.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Biometrics; Computational Intelligence; Neural Networks; Fingerprint; Iris; Face
Elenco autori:
R. Donida Labati, A. Genovese, E. Munoz Ballester, V. Piuri, F. Scotti, G. Sforza
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