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What you'll be able to do (official learning outcomes)
discuss biometric algorithms and data analysis along with digital image/signal processing; Computing 74 New
apply automated biometric identification: hands-fingers, palms and hands; heads-face, voice and eyes and other biometrics
develop methods of obtaining biometric data and matching basics
create storage of biometric data elements, quality, upgrades, data security and integrity
analyse privacy issues, security strength, recognition rates and other aspects of biometrics, passwords and smart cards; and
explore applications of biometrics and future trends
Course contents
Introduction to biometrics and digital image processing. Matlab in biometric image/signal processing. Biometric algorithms and systems with emphasis on face, fingerprint, eyes (iris), speech (voice). Automated biometric identification multimodal biometrics. Biometric data: raw data, template data, and data methods.
Source: the Nigerian Universities Commission (NUC) Core Curriculum and Minimum Academic Standards (CCMAS). StudyOps loads this syllabus automatically when you study CYB 302.