Course detail

Biometric Systems

FIT-BIOAcad. year: 2020/2021

Theory of the signal processing, especially image signal processing, for the purposes of the biometry. Introduction of the basic methods and techniques of the static single biometric features: fingerprint, hand geometry, face and its thermogram, iris, retina, handwriting. Recognition using the dynamic features: lip movements, typing or gait. Standards in the biometry. Applications of the biometry.

Guarantor

prof. Ing. Martin Drahanský, Ph.D.

Department

Department of Intelligent Systems (UITS)

Learning outcomes of the course unit

Theory of the signal processing, functionality of different biometric technologies and of their importance in the IT security, including systems for the police purposes. Knowledge of the methods of the biometric systems evaluation.

Prerequisites

  • Student should be familiar with the basics of the 1- and 2-dimensional signal processing.
  • Valid schooling of Edict No. 50 (work with electrical devices) is needed.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Literature

Ashbourn, J.: Practical Biometrics - From Aspiration to Implementation, Springer Verlag, 2004, ISBN 1-85233-774-5
Drahanský, M.: Hand-Based Biometrics: Methods and Technology. London: The Institution of Engineering and Technology, 2018. ISBN 978-1-78561-224-4 (k dostání v knihovně FIT/available in FIT library)
Bhanu, B., Tan, X.: Computational Algorithms for Fingerprint Recognition, Kluwer Academic Publishers, USA, 2004, ISBN 1-4020-7651-7
Drahanský, M., Orság, F. a kol.: Biometrie, Computer Press, 2011, ISBN 978-80-254-8979-6 (k dostání v knihovně FIT/available in FIT library)
Ashbourn, J.: Practical Biometrics - From Aspiration to Implementation, Springer Verlag, 2004, ISBN 1-85233-774-5
Bolle, R.M., Connell, J.H., Pankanti, S., Ratha, N.K., Senior, A.W.: Guide to Biometrics, Springer Verlag, 2004, ISBN 0-387-40089-3
Bolle, R.M., Connell, J.H., Pankanti, S., Ratha, N.K., Senior, A.W.: Guide to Biometrics, Springer Verlag, 2004, ISBN 0-387-40089-3
Drahanský, M.: Hand-Based Biometrics: Methods and Technology. London: The Institution of Engineering and Technology, 2018. ISBN 978-1-78561-224-4
Drahanský, M., Orság, F., Doležel, M. a kol.: Biometrie, Brno, CZ, Computer Press, 2011, ISBN 978-80-254-8979-6
Chetty, G., Yang, J.: Advanced Biometric Technologies, InTech, 2011, p. 394, ISBN 978-953-307-487-0.
Chirillo, J., Blaul, S.: Implementing Biometric Security, Wiley Publishing, 2003, ISBN 0-7645-2502-6
Nanavati, S., Thieme, M., Nanavati, R.: Biometrics - Identity Verification in a Networked World, Wiley Publishing, 2002, ISBN 0-471-09945-7
Yang, J.: Biometrics, InTech, 2011, p. 278, ISBN 978-953-307-618-8.
Nanavati, S., Thieme, M., Nanavati, R.: Biometrics - Identity Verification in a Networked World, Wiley Publishing, 2002, ISBN 0-471-09945-7
Yang, J., Nanni, L.: State of the Art in Biometrics, InTech, 2011, p. 326, ISBN 978-953-307-489-4.
Woodward, J.D., Orlans, N.M., Higgins, P.T.: Biometrics - Identity Assurance in the Information Age, McGraw-Hill Osborne Media, 2002, ISBN 007-222227-1

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

  1. Mid-term written test.
  2. Attending of the laboratory seminars.
  3. Project.

Exam prerequisites:
Student must gain at least 15 points during the term and at the same time at least 3 points student must get for project.

Language of instruction

Czech, English

Work placements

Not applicable.

Aims

To learn the actual biometric technologies (fingerprint, eye retina, eye iris, DNA etc.) and their application in the IT and in the security systems. To learn methods for evaluation of the reliability and quality of the biometric systems, including biometric standards.

Specification of controlled education, way of implementation and compensation for absences

Mid-term exam, presence in the laboratory practice, projects and final exam are monitored and given points for. There is no way to obtain the points for the mid-term exam, project after the deadline and laboratory practice additionally. Final exam has two additional correction possibilities.

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MPV , any year of study, winter semester, 5 credits, elective
    branch MGM , any year of study, winter semester, 5 credits, elective
    branch MSK , any year of study, winter semester, 5 credits, elective
    branch MIS , any year of study, winter semester, 5 credits, elective
    branch MIN , any year of study, winter semester, 5 credits, compulsory-optional
    branch MMI , any year of study, winter semester, 5 credits, elective
    branch MMM , any year of study, winter semester, 5 credits, elective

  • Programme MITAI Master's

    specialization NADE , any year of study, winter semester, 5 credits, elective
    specialization NBIO , any year of study, winter semester, 5 credits, elective
    specialization NGRI , any year of study, winter semester, 5 credits, elective
    specialization NNET , any year of study, winter semester, 5 credits, elective
    specialization NVIZ , any year of study, winter semester, 5 credits, elective
    specialization NCPS , any year of study, winter semester, 5 credits, elective
    specialization NSEC , any year of study, winter semester, 5 credits, compulsory
    specialization NEMB , any year of study, winter semester, 5 credits, elective
    specialization NHPC , any year of study, winter semester, 5 credits, elective
    specialization NISD , any year of study, winter semester, 5 credits, elective
    specialization NIDE , any year of study, winter semester, 5 credits, elective
    specialization NISY , any year of study, winter semester, 5 credits, elective
    specialization NMAL , any year of study, winter semester, 5 credits, elective
    specialization NMAT , any year of study, winter semester, 5 credits, elective
    specialization NSEN , any year of study, winter semester, 5 credits, elective
    specialization NVER , any year of study, winter semester, 5 credits, elective
    specialization NSPE , any year of study, winter semester, 5 credits, elective

  • Programme IT-MGR-2 Master's

    branch MBI , 1. year of study, winter semester, 5 credits, compulsory
    branch MBS , 2. year of study, winter semester, 5 credits, compulsory

Type of course unit

 

Lecture

39 hours, optionally

Teacher / Lecturer

prof. Ing. Martin Drahanský, Ph.D.
Ing. Michal Dvořák
Ing. Tomáš Goldmann
Mona Heidari
Ing. Ondřej Kanich, Ph.D.
Ing. Radim Pernický
Ing. Lukáš Semerád

Syllabus

  1. Introduction to the biometric systems
  2. Theory of the sound and image signal processing
  3. Evaluation of the reliability and quality of the biometric systems
  4. Fingerprint recognition
  5. Liveness detection on fingers
  6. Hand geometry, veins and nail recognition
  7. Face and face thermogram recognition
  8. Iris and retina recognition
  9. Handwriting and signature recognition
  10. Dynamic biometric characteristics
  11. DNA and its application in the biometry
  12. Biometric standards
  13. Biometric systems of the future

Laboratory exercise

6 hours, compulsory

Teacher / Lecturer

Ing. Michal Dvořák
Ing. Tomáš Goldmann
Mona Heidari
Ing. Ondřej Kanich, Ph.D.
Andrii Kavetskyi
Ing. Radim Pernický
Ing. Štěpán Rydlo
Ing. Martin Sakin
Ing. Lukáš Semerád
Ing. Jan Tinka

Syllabus

  1. Fingerprint recognition, dactyloscopy, work with sensors, spoofing, liveness detection
  2. Eye retina and eye iris, 3D face model
  3. Signature and its spoofing, 2D and 3D hand geometry, recognition of hand veins, thermograms of face and hand

Project

7 hours, compulsory

Teacher / Lecturer

Ing. Michal Dvořák
Ing. Tomáš Goldmann
Mona Heidari
Ing. Ondřej Kanich, Ph.D.
Andrii Kavetskyi
Ing. Radim Pernický
Ing. Štěpán Rydlo
Ing. Martin Sakin
Ing. Lukáš Semerád
Ing. Jan Tinka

Syllabus

Exact specification will be published within the semester. It will be possible to choose from the following categories:
  • Fingerprint recognition
  • Liveness detection
  • Hand geometry, veins and nail recognition
  • Face and face thermogram recognition
  • Iris and retina recognition
  • Handwriting and signature recognition
  • Dynamic biometrical characteristics
  • DNA and its application in the biometry
  • Biometrical standards