ECTS - Digital Image Processing
Digital Image Processing (CMPE464) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
---|---|---|---|---|---|---|---|
Digital Image Processing | CMPE464 | Area Elective | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Technical Elective Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture. |
Course Lecturer(s) |
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Course Objectives | The main aim of the course is : to give an introduction to 1-D and 2-D signals, to give introduction to spatial domain and frequency domain of signals to give an introduction to theories and mathematical methods used in image analysis, to introduce the analytical tools and methods which are currently used in digital image processing, and to make the students to apply these tools in the laboratory in image restoration, enhancement and compression. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Introduction to signal and image processing, introduction to digital image processing, sampling, reconstruction, and quantization, digital image representation, image transforms, enhancement, restoration, segmentation and description. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Introduction to signals and systems | Other sources |
2 | 1-D and 2-D Signals and signal processing | Other source |
3 | Sampling and quantization of 2-D signals | Other source |
4 | Introduction to Digital Images, and image processing applications | Ch.1 (main text) |
5 | Fundamentals of image processing | Ch.1-2 (main text) |
6 | Intensity Transformations and Spatial Filtering | Ch. 2 |
7 | Processing of 1-D and 2-D signals, and processing in the frequency domain, mathematical fundamentals of fast fourier transform | Ch. 2 |
8 | Image Enhancement | Ch.3, Ch. 4 |
9 | Image Restoration | Ch.5 |
10 | Color Image Processing | Ch. 6 |
11 | Image Compression | Ch.8 |
12 | Morphological Image Processing | Ch.9 |
13 | Image Segmentation | Ch.10 |
14 | Object Recognition. | Ch.12 |
Sources
Course Book | 1. Gonzalez, R. C., Woods, R. E., Digital Image Processing, Addison-Wesley, 2008. |
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Other Sources | 2. 1. Jain, A. K., Fundamentals of digital Image Processing, Prentice-Hall. |
3. 2. Castleman, K. R., Digital Image Processing, Prentice Hall. | |
4. 3. John G. Prokis and Dimitris G. Manolakis, “Digital Signal Processing: Principle, Algorithms and Applications” Prentice Hall Inc., Englewood Cliffs, NJ (USA), 3rd Ed., 1996. |
Evaluation System
Requirements | Number | Percentage of Grade |
---|---|---|
Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | 5 | 30 |
Presentation | - | - |
Project | - | - |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 1 | 35 |
Final Exam/Final Jury | 1 | 35 |
Toplam | 7 | 100 |
Percentage of Semester Work | 65 |
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Percentage of Final Work | 35 |
Total | 100 |
Course Category
Core Courses | |
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Major Area Courses | X |
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 subjects specific to the computer engineering discipline; the ability to apply theoretical and practical knowledge of these areas to complex engineering problems. | X | ||||
2 | The ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. | X | ||||
3 | The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. | |||||
4 | The ability to develop, select and utilize modern techniques and tools essential for the analysis and determination of complex problems in computer engineering applications; the ability to utilize information technologies effectively. | |||||
5 | The ability to design experiments, conduct experiments, gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the computer engineering discipline. | |||||
6 | The ability to work effectively in inter/inner disciplinary teams; ability to work individually | |||||
7 | Effective oral and writen communication skills in Turkish; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions. | |||||
8 | The knowledge of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions. | |||||
9 | Recognition of the need for lifelong learning; the ability to access information, to follow recent developments in science and technology. | |||||
10 | The ability to behave according to ethical principles, awareness of professional and ethical responsibility; | |||||
11 | Knowledge of the standards utilized in software engineering applications | |||||
12 | Knowledge on business practices such as project management, risk management and change management; | |||||
13 | Awareness about entrepreneurship, innovation | |||||
14 | Knowledge on sustainable development | |||||
15 | Knowledge on the effects of computer engineering applications on the universal and social dimensions of health, environment and safety; | |||||
16 | Awareness of the legal consequences of engineering solutions | |||||
17 | An ability to describe, analyze and design digital computing and representation systems. | |||||
18 | An ability to use appropriate computer engineering concepts and programming languages in solving computing problems. | X |
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 | 1 | 16 |
Presentation/Seminar Prepration | |||
Project | |||
Report | |||
Homework Assignments | 5 | 8 | 40 |
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 1 | 10 | 10 |
Prepration of Final Exams/Final Jury | 1 | 15 | 15 |
Total Workload | 129 |