| Code |
11507
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| Year |
1
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| Semester |
S1
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| ECTS Credits |
6
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| Workload |
OT(15H)
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| Scientific area |
Informatics
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|
Entry requirements |
Previous knowledge in Artificial Intelligence and Pattern recognition areas. Solid notions of Programming.
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Mode of delivery |
Face-to-face
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|
Work placements |
(Not applicable)
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Learning outcomes |
Understanding of the main concepts related to biometric systems. Identification of the several phases associated to the biometric recognition process: detection of the region of interest, data segmentation, normalization, codification and matching. Classification of a biometric system according to different performance measures.
Ability to identify requisites, plan and implement a biometric system: selection of the biometric trait to be used, planning of the data acquisition framework and protocol. Identification of data variation factors. definition of methods for noise handling. Implementation and optimization of biometric systems.
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Syllabus |
Introduction to biometrics. Biometric traits: comparison according to different perspectives. A biometric system as a pattern recognition application: data acquisition, segmentation and data normalization. feature extraction and matching. Histograms of genuine and impostors comparisons (variability). performance measures of biometric systems (ROC, DET, EER, FRR|FAR=0). Fusion of biometric systems. Fusion at different levels.
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Main Bibliography |
Handbook of Biometrics; Anil K. Jain (Editor), Patrick Flynn (Editor), Arun A. Ross (Editor); Springer; 1 edition (October 29, 2007), ISBN-13: 978-0387710402.
Advances in Biometrics: Sensors, Algorithms and Systems, N. K. Ratha (Editor), Venu Govindaraju (Editor); Springer; 1 edition (November 7, 2007), ISBN-13: 978-1846289200,
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Language |
Portuguese. Tutorial support is available in English.
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