Course Detail
Course Description
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|---|---|---|---|---|
INTRODUCTION to BIOMETRIC SYSTEMS | COE4115413 | Fall Semester | 3+3 | 4,5 | 6 |
Course Program | Çarşamba 15:30-16:15 Çarşamba 16:30-17:15 Çarşamba 17:30-18:15 |
Prerequisites Courses | |
Recommended Elective Courses |
Language of Course | English |
Course Level | First Cycle (Bachelor's Degree) |
Course Type | Elective |
Course Coordinator | Prof.Dr. Mehmet Kemal ÖZDEMİR |
Name of Lecturer(s) | Lect.Dr. Umut ULUDAĞ |
Assistant(s) | Lecture Notes |
Aim | Biometric systems, that rely on physiological and/or behavioral characteristics (e.g., fingerprint, face, iris, voice ...), for personal authentication, are becoming ubiquitous: from national e-ID cards, to accessing secure sites (e.g. airports), from web-based applications to law enforcement checks (e.g. AFIS), these systems that go beyond the usage of traditional username/password/card combinations are securing our lives & creating added value every day. In this course, design, implementation, and evaluation of unimodal & multimodal biometric systems with primers on relevant signal processing & pattern recognition topics will be covered. The intersection with cryptography and future prospects will also be highlighted. |
Course Content | This course contains; Introduction to biometric systems, general characteristics, building blocks, applications,Identity verification methods: biometrics based and others,Relevant pattern recognition and signal processing topics, feature extractors & classifiers ,Parmakizi tanıma: sensörler, öznitelikler, başarım, sınıflandırma, indeksleme, tekillik,Fingerprint recognition, features, performance, classification, indexing, and uniqueness. ,Face recognition,Iris recognition,Exam Week - Midterm,Voice recognition,Gait, vein, palmprint, signature recognition & novel modalities,Multimodal biometric systems,Cryptography & biometrics: system security & template privacy,Standard databases, evaluation & tests,Future prospects, research directions, challenges; project evaluations,Future prospects, research directions, challenges; project evaluations. |
Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
1. Understand design principles for a biometric system, appropriate for a given set of requirements | 9 | A, E, F |
2. Evaluate alternative biometric systems, in terms of accuracy, cost, practicality | 9 | A, E, F |
3. Learn how to assist software developers in implementing a successful biometric system | 9 | A, E, F |
4. Make informed decisions considering limitations and advantages of biometric systems, with respect to traditional identity verification systems | 9 | A, E, F |
Teaching Methods: | 9: Lecture Method |
Assessment Methods: | A: Traditional Written Exam, E: Homework, F: Project Task |
Course Outline
Order | Subjects | Preliminary Work |
---|---|---|
1 | Introduction to biometric systems, general characteristics, building blocks, applications | Ref.1 Ch. 1 |
2 | Identity verification methods: biometrics based and others | Ref. 1 Ch. 1 |
3 | Relevant pattern recognition and signal processing topics, feature extractors & classifiers | Ref. 4 Ch. 1 |
4 | Parmakizi tanıma: sensörler, öznitelikler, başarım, sınıflandırma, indeksleme, tekillik | Ref. 2 Ch. 2-4, 5, 8 |
5 | Fingerprint recognition, features, performance, classification, indexing, and uniqueness. | Ref. 2 Ch. 2-4, 5, 8 |
6 | Face recognition | Ref.1 Ch. 3 |
7 | Iris recognition | Ref.1 Ch. 4 |
8 | Exam Week - Midterm | Lectures till Week 7 |
9 | Voice recognition | Ref.1 Ch. 8 |
10 | Gait, vein, palmprint, signature recognition & novel modalities | Ref.1 Ch. 6&9&10 |
11 | Multimodal biometric systems | Ref.3 Ch. 2&3 |
12 | Cryptography & biometrics: system security & template privacy | Ref.1 Ch. 19 |
13 | Standard databases, evaluation & tests | Ref.1 Ch. 24&25 |
14 | Future prospects, research directions, challenges; project evaluations | Publication websites |
15 | Future prospects, research directions, challenges; project evaluations | Publication websites |
Resources |
A.K. Jain, P. Flynn, A.A. Ross, Handbook of Biometrics, Springer, 2008. |
1- D. Maltoni, D. Maio, A.K. Jain, and S. Prabhakar, Handbook of Fingerprint Recognition, 2. Ed., Springer, 2009. 2- A. Ross, K. Nandakumar, and A.K. Jain, Handbook of Multibiometrics, 2006. 3- R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification, 2. Ed., Wiley, 2001. |
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications | |||||||
No | Program Qualification | Contribution Level | |||||
1 | 2 | 3 | 4 | 5 | |||
1 | 1. An ability to apply knowledge of mathematics, science, and engineering | X | |||||
2 | 2. An ability to identify, formulate, and solve engineering problems | X | |||||
3 | 3. An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability | X | |||||
4 | 4. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | X | |||||
5 | 5. An ability to design and conduct experiments, as well as to analyze and interpret data | X | |||||
6 | 6. An ability to function on multidisciplinary teams | X | |||||
7 | 7. An ability to communicate effectively | X | |||||
8 | 8. A recognition of the need for, and an ability to engage in life-long learning | X | |||||
9 | 9. An understanding of professional and ethical responsibility | X | |||||
10 | 10. A knowledge of contemporary issues | X | |||||
11 | 11. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context | X |
Assessment Methods
Contribution Level | Absolute Evaluation | |
Rate of Midterm Exam to Success | 30 | |
Rate of Final Exam to Success | 70 | |
Total | 100 |
ECTS / Workload Table | ||||||
Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
Course Hours | 14 | 3 | 42 | |||
Guided Problem Solving | 0 | 0 | 0 | |||
Resolution of Homework Problems and Submission as a Report | 8 | 5 | 40 | |||
Term Project | 14 | 2 | 28 | |||
Presentation of Project / Seminar | 2 | 10 | 20 | |||
Quiz | 0 | 0 | 0 | |||
Midterm Exam | 1 | 18 | 18 | |||
General Exam | 1 | 24 | 24 | |||
Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
Total Workload(Hour) | 172 | |||||
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(172/30) | 6 | |||||
ECTS of the course: 30 hours of work is counted as 1 ECTS credit. |
Detail Informations of the Course
Course Description
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|---|---|---|---|---|
INTRODUCTION to BIOMETRIC SYSTEMS | COE4115413 | Fall Semester | 3+3 | 4,5 | 6 |
Course Program | Çarşamba 15:30-16:15 Çarşamba 16:30-17:15 Çarşamba 17:30-18:15 |
Prerequisites Courses | |
Recommended Elective Courses |
Language of Course | English |
Course Level | First Cycle (Bachelor's Degree) |
Course Type | Elective |
Course Coordinator | Prof.Dr. Mehmet Kemal ÖZDEMİR |
Name of Lecturer(s) | Lect.Dr. Umut ULUDAĞ |
Assistant(s) | Lecture Notes |
Aim | Biometric systems, that rely on physiological and/or behavioral characteristics (e.g., fingerprint, face, iris, voice ...), for personal authentication, are becoming ubiquitous: from national e-ID cards, to accessing secure sites (e.g. airports), from web-based applications to law enforcement checks (e.g. AFIS), these systems that go beyond the usage of traditional username/password/card combinations are securing our lives & creating added value every day. In this course, design, implementation, and evaluation of unimodal & multimodal biometric systems with primers on relevant signal processing & pattern recognition topics will be covered. The intersection with cryptography and future prospects will also be highlighted. |
Course Content | This course contains; Introduction to biometric systems, general characteristics, building blocks, applications,Identity verification methods: biometrics based and others,Relevant pattern recognition and signal processing topics, feature extractors & classifiers ,Parmakizi tanıma: sensörler, öznitelikler, başarım, sınıflandırma, indeksleme, tekillik,Fingerprint recognition, features, performance, classification, indexing, and uniqueness. ,Face recognition,Iris recognition,Exam Week - Midterm,Voice recognition,Gait, vein, palmprint, signature recognition & novel modalities,Multimodal biometric systems,Cryptography & biometrics: system security & template privacy,Standard databases, evaluation & tests,Future prospects, research directions, challenges; project evaluations,Future prospects, research directions, challenges; project evaluations. |
Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
1. Understand design principles for a biometric system, appropriate for a given set of requirements | 9 | A, E, F |
2. Evaluate alternative biometric systems, in terms of accuracy, cost, practicality | 9 | A, E, F |
3. Learn how to assist software developers in implementing a successful biometric system | 9 | A, E, F |
4. Make informed decisions considering limitations and advantages of biometric systems, with respect to traditional identity verification systems | 9 | A, E, F |
Teaching Methods: | 9: Lecture Method |
Assessment Methods: | A: Traditional Written Exam, E: Homework, F: Project Task |
Course Outline
Order | Subjects | Preliminary Work |
---|---|---|
1 | Introduction to biometric systems, general characteristics, building blocks, applications | Ref.1 Ch. 1 |
2 | Identity verification methods: biometrics based and others | Ref. 1 Ch. 1 |
3 | Relevant pattern recognition and signal processing topics, feature extractors & classifiers | Ref. 4 Ch. 1 |
4 | Parmakizi tanıma: sensörler, öznitelikler, başarım, sınıflandırma, indeksleme, tekillik | Ref. 2 Ch. 2-4, 5, 8 |
5 | Fingerprint recognition, features, performance, classification, indexing, and uniqueness. | Ref. 2 Ch. 2-4, 5, 8 |
6 | Face recognition | Ref.1 Ch. 3 |
7 | Iris recognition | Ref.1 Ch. 4 |
8 | Exam Week - Midterm | Lectures till Week 7 |
9 | Voice recognition | Ref.1 Ch. 8 |
10 | Gait, vein, palmprint, signature recognition & novel modalities | Ref.1 Ch. 6&9&10 |
11 | Multimodal biometric systems | Ref.3 Ch. 2&3 |
12 | Cryptography & biometrics: system security & template privacy | Ref.1 Ch. 19 |
13 | Standard databases, evaluation & tests | Ref.1 Ch. 24&25 |
14 | Future prospects, research directions, challenges; project evaluations | Publication websites |
15 | Future prospects, research directions, challenges; project evaluations | Publication websites |
Resources |
A.K. Jain, P. Flynn, A.A. Ross, Handbook of Biometrics, Springer, 2008. |
1- D. Maltoni, D. Maio, A.K. Jain, and S. Prabhakar, Handbook of Fingerprint Recognition, 2. Ed., Springer, 2009. 2- A. Ross, K. Nandakumar, and A.K. Jain, Handbook of Multibiometrics, 2006. 3- R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification, 2. Ed., Wiley, 2001. |
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications | |||||||
No | Program Qualification | Contribution Level | |||||
1 | 2 | 3 | 4 | 5 | |||
1 | 1. An ability to apply knowledge of mathematics, science, and engineering | X | |||||
2 | 2. An ability to identify, formulate, and solve engineering problems | X | |||||
3 | 3. An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability | X | |||||
4 | 4. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | X | |||||
5 | 5. An ability to design and conduct experiments, as well as to analyze and interpret data | X | |||||
6 | 6. An ability to function on multidisciplinary teams | X | |||||
7 | 7. An ability to communicate effectively | X | |||||
8 | 8. A recognition of the need for, and an ability to engage in life-long learning | X | |||||
9 | 9. An understanding of professional and ethical responsibility | X | |||||
10 | 10. A knowledge of contemporary issues | X | |||||
11 | 11. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context | X |
Assessment Methods
Contribution Level | Absolute Evaluation | |
Rate of Midterm Exam to Success | 30 | |
Rate of Final Exam to Success | 70 | |
Total | 100 |