ECTS - Digital Image Processing
Digital Image Processing (EE421) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Digital Image Processing | EE421 | Area Elective | 2 | 2 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| MATH275 |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Discussion, Experiment, Question and Answer, Drill and Practice, Team/Group, Brain Storming. |
| Course Lecturer(s) |
|
| Course Objectives | •Study the image fundamentals and mathematical transforms necessary for image processing. •Study the image enhancement techniques •Study image restoration procedures. •Study the image compression procedures. •Study the image segmentation and representation techniques |
| Course Learning Outcomes |
The students who succeeded in this course;
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| Course Content | 2-D systems and transforms, image acquisition, sampling and quantization, linear and non-linear techniques for image enhancement and restoration and image compression, differential pulse code modulation, vector quantization, wavelets, subband coding, still and video compression coding standards. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Digital Image Fundamentals and Transforms | Glance this week’s topics from the lecture |
| 2 | Image Enhancement in the Spatial Domain •Gray Level Transformations •Histogram Processing •Spatial Filtering | Review last week and glance this week’s topics from the lecture |
| 3 | Image Enhancement in the Spatial Domain •Smoothing Spatial Filters •Sharpening Spatial Filters | Review last week and glance this week’s topics from the lecture |
| 4 | Image Enhancement in the Frequency Domain •Fourier Transform and Frequency Domain •Smoothing Frequency Domain Filters •Sharpening Frequency Domain Filters | Review last week and glance this week’s topics from the lecture |
| 5 | Image Enhancement in the Frequency Domain •Homomorphic Filtering •Implementation | Review last week and glance this week’s topics from the lecture |
| 6 | Image Restoration Techniques •Degradation Model •Inverse Filtering •Wiener Filtering | Glance this week’s topics from the lecture |
| 7 | Image Restoration Techniques | Review last week and glance this week’s topics from the lecture |
| 8 | Image Segmentation •Detection of Discontinuities •Edge Linking and Boundary Detection •Thresholding | Glance this week’s topics from the lecture |
| 9 | Image Segmentation •Region Based Segmentation •The use motion in Segmentation | Review last week and glance this week’s topics from the lecture |
| 10 | Image Compression •Image Compression Models •Elements of Information Theory •Error-Free Compression •Lossy Compression •Image Compression Standards | Glance this week’s topics from the lecture |
| 11 | Morphological Image Processing •Dilation and Erosion •Opening And Closing •Morphological Algorithms | Glance this week’s topics from the lecture |
| 12 | Representation and Description •Representation •Boundary Descriptors •Regional Descriptors | Glance this week’s topics from the lecture |
| 13 | Representation and Description •Use of Principle of Components for Description | Review last week and glance this week’s topics from the lecture |
| 14 | Object Recognition •Patterns and Pattern Classes •Matching, Optimum Statistical Classifiers | Glance this week’s topics from the lecture |
| 15 | Final examination period | Review topics |
| 16 | Final examination period | Review topics |
Sources
| Course Book | 1. Digital Image Processing,2nd Edition, Rafael C. Gonzales and Richard E. Woods, Pearson Education, 2003. |
|---|---|
| Other Sources | 2. Two-Dimensional Signal and Image Processing, Jae S. Lim, Prentice-Hall, 1989. |
| 3. Digital Video Processing, A. Murat Tekalp, Prentice-Hall, 1995. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | 9 | 15 |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | 1 | 15 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 40 |
| Final Exam/Final Jury | 1 | 30 |
| Toplam | 12 | 100 |
| Percentage of Semester Work | 70 |
|---|---|
| Percentage of Final Work | 30 |
| 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 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | X | ||||
| 2 | Ability to formulate, and solve complex mechatronics engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | X | ||||
| 3 | Ability to design a complex mechatronics engineering system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | X | ||||
| 4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in mechatronics engineering and robot technology practices; ability to employ information technologies effectively. | X | ||||
| 5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex mechatronics engineering and robot technology problems or research questions. | X | ||||
| 6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | X | ||||
| 7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | X | ||||
| 8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself | X | ||||
| 9 | a-) Knowledge on behavior according to ethical principles, professional and ethical responsibility b-) Knowledge on standards used in engineering practices. | |||||
| 10 | a-) Knowledge about business life practices such as project management, risk management, and change management b-) Awareness in entrepreneurship, innovation; knowledge about sustainable development. | |||||
| 11 | Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. | |||||
| 12 | Competency on defining, analyzing and surveying databases and other sources, proposing solutions based on research work and scientific results and communicate and publish numerical and conceptual solutions in the field of mechatronics engineering. | |||||
| 13 | Consciousness on the environment and social responsibility, competencies on observation, improvement and modify and implementation of projects for the society and social relations and be an individual within the society in such a way that planning, improving or changing the norms with a criticism. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | 6 | 2 | 12 |
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 2 | 28 |
| Presentation/Seminar Prepration | 2 | 2 | 4 |
| Project | 1 | 20 | 20 |
| Report | |||
| Homework Assignments | 7 | 2 | 14 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 2 | 4 |
| Prepration of Final Exams/Final Jury | 1 | 2 | 2 |
| Total Workload | 132 | ||