ECTS - Advanced Topics in Digital Image Processing
Advanced Topics in Digital Image Processing (MDES672) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Advanced Topics in Digital Image Processing | MDES672 | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| Consent of the Instructor |
| Course Language | English |
|---|---|
| Course Type | N/A |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| Course Objectives | Upon successful completion of the course, students will learn and have an understanding of the mathematical tools for modeling and analysis of image acquisition and processing systems. Students will also master basic techniques of image processing applications. |
| Course Learning Outcomes |
The students who succeeded in this course;
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| Course Content | Review of image processing fundamentals, frequency and space domain image processing methods; wavelets, multiresolution processing, and orthogonal transforms; image and video compression standards; image segmentation and representation; nonlinear image processing methods. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Review of image processing fundamentals | Related pages of lecture notes and other sources |
| 2 | Review of basic frequency and space domain image processing techniques | Related pages of lecture notes and other sources |
| 3 | Review of basic frequency and space domain image processing techniques | Related pages of lecture notes and other sources |
| 4 | Subband decomposition, filter banks, and pyramids | Related pages of lecture notes and other sources |
| 5 | Subband decomposition, filter banks, and pyramids | Related pages of lecture notes and other sources |
| 6 | Wavelets and discrete orthogonal transforms | Related pages of lecture notes and other sources |
| 7 | Wavelets and discrete orthogonal transforms | Related pages of lecture notes and other sources |
| 8 | Nonlinear image processing techniques | Related pages of lecture notes and other sources |
| 9 | Nonlinear image processing techniques | Related pages of lecture notes and other sources |
| 10 | Image segmentation | Related pages of lecture notes and other sources |
| 11 | Image representation and Description | Related pages of lecture notes and other sources |
| 12 | Image representation and Description | Related pages of lecture notes and other sources |
| 13 | Object Recognition | Related pages of lecture notes and other sources |
| 14 | Object Recognition | Related pages of lecture notes and other sources |
| 15 | Overall review | - |
| 16 | Final exam | - |
Sources
| Course Book | 1. Ders notları / Notes are available |
|---|---|
| Other Sources | 2. 1. Digital Image Processing, Rafael C. Gonzales and Richard E. Woods, Addison-Wesley Publishing Company, 1993. |
| 3. 2. Digital Video Processing, A. Murat Tekalp, Prentice-Hall, 1995. | |
| 4. 3. Two-Dimensional Signal and Image Processing, Jae S. Lim, Prentice-Hall, 1989. | |
| 5. 4. Fundamentals of Digital Image Processing, Anil K. Jain and Thomas Kailath, Prentice-Hall 1988. | |
| 6. 5. Digital Image Processing, Kenneth R. Castleman, Prentice-Hall, 1995. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | 4 | 20 |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | 2 | 40 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 20 |
| Final Exam/Final Jury | 1 | 20 |
| Toplam | 9 | 100 |
| Percentage of Semester Work | 80 |
|---|---|
| Percentage of Final Work | 20 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Ability to expand and get in-depth information with scientific researches in the field of mechanical engineering, evaluate information, review and implement. | |||||
| 2 | Have comprehensive knowledge about current techniques and methods and their limitations in Mechanical engineering. | |||||
| 3 | To complete and apply knowledge by using scientific methods using uncertain, limited or incomplete data; use information from different disciplines. | |||||
| 4 | Being aware of the new and developing practices of Mechanical Engineering and being able to examine and learn when needed. | |||||
| 5 | Ability to define and formulate problems related to Mechanical Engineering and develop methods for solving and apply innovative methods in solutions. | |||||
| 6 | Ability to develop new and/or original ideas and methods; design complex systems or processes and develop innovative/alternative solutions in the designs. | |||||
| 7 | Ability to design and apply theoretical, experimental and modeling based researches; analyze and solve complex problems encountered in this process. | |||||
| 8 | Work effectively in disciplinary and multi-disciplinary teams, lead leadership in such teams and develop solution approaches in complex situations; work independently and take responsibility. | |||||
| 9 | To establish oral and written communication by using a foreign language at least at the level of European Language Portfolio B2 General Level. | |||||
| 10 | Ability to convey the process and results of their studies systematically and clearly in written and oral form in national and international environments. | |||||
| 11 | To know the social, environmental, health, security, law dimensions, project management and business life applications of engineering applications and to be aware of the constraints of their engineering applications. | |||||
| 12 | Ability to observe social, scientific and ethical values in the stages of data collection, interpretation and announcement and in all professional activities. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 2 | 32 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | 4 | 5 | 20 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 8 | 16 |
| Prepration of Final Exams/Final Jury | 1 | 10 | 10 |
| Total Workload | 126 | ||