1 / 15

Biometrics Module Overview & Learning Outcomes in Signals & Systems

Explore biometric technologies, mathematical techniques for pattern recognition, and digital signal processing algorithms in this module. Learn about fingerprint, facial, and iris scans, speech processing, and privacy risks associated with biometrics.

lethia
Télécharger la présentation

Biometrics Module Overview & Learning Outcomes in Signals & Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CA614 Biometrics • Welcome • Today • Admin • Module overview • Some signals

  2. Admin • Lectures • John McKenna, john@computing.dcu.ie Office: 2.47, Tel. (700)5507 • Alistair Sutherland, Lecturer • Monday 11pm, Q120 • Wednesday 9am, X130 • Labs • Monday 4-6pm, LG.01 • Andrew Errity, Tutor • Michelle Tooher, Tutor

  3. Admin • Prerequisites • Some maths • probability, linear algebra (matrices), complex numbers • Ability to program • Open mind • Please come see me if you have doubts about prerequisite knowledge

  4. Admin • Assessment • Continuous Assessment: 30% • Assignment: Speaker/Face/Signature Verification • End of module exam: 70% • Books, etc • See Module Descriptor for list • No book purchase necessary • Recommended • Headset required • Composite (with microphone) recommended • Sharing feasible & recommended

  5. What is Biometrics? • “Life measurement” • “ Biometric technologies are automated methods of verifying or recognising the identity of a living person based on a physical or behavioural characteristic”, • Ben Miller, 1987

  6. Projections I Frost & Sullivan (1990)

  7. Projections II IBG Forecast (2000)

  8. Projections III IBIA Forcast (2000)

  9. Module Overview • Module Aims • To cover all modern approaches to biometrics, in the context of automatic computerised methods of identifying an individual based on who they really are - using a variety of attributes such as finger-prints, iris scans etc.

  10. Indicative Syllabus I • Generic mathematical techniques for pattern recognition and digital filtering. • Frequency domain analysis - Fourier and other transforms. • Digital signal processing algorithms. • Benefits of biometrics to identification systems. • Enrolment and template creation. • Accuracy in Biometric systems. False match rates and false non-match rates. • Derived metrics

  11. Indicative Syllabus II • Fingerprint scan. Image acquisition and processing. Competing technologies. Finger scan problems. • Facial scan. Image acquisition and processing. • Iris scan. Image acquisition and processing. • Voice Scan. Speech processing. Implementation of speech processing algorithms. • Other physiological biometrics - signature and key-stroke scanning. • Multifactor identification. • Privacy risks of biometrics.

  12. Learning Outcomes • Awareness of the practicability and applicability of modern method of biometrics. • That an individual's identity can be ascertained to a very high degree of confidence using appropriate sensors and systems. • The common mathematics of pattern recognitionthat underpins this technology. • An understanding of signals: waveforms & spectra • Competence at implementing verification algorithms • Ability to program MATLAB scripts • Ability to use HTK (Hidden Markov Model Toolkit) for verification design

  13. Module Overview • Achieving the aims of the modulewill involve the following: • Communication skills • Group Work skills • Organisational skills • Personal skills • Problem solving skills • Programming skills • Information Technology skills • Cross-disciplinary partnerships • Skills transfer • Module mailing list • Discussion forum; No code!!!

  14. A Taste of Things to Come • Today’s Lab • Speech Waveforms & Spectra • Matlab Intro • Now • Demos • Next • Authentication technologies

  15. Rough Plan • Intro/Background • Maths • Technologies • Issues

More Related