TÜRKÇE
ENGLISH
Information
| Code | CEN403 |
| Name | Digital Image Processing |
| Term | 2024-2025 Academic Year |
| Semester | 7. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. MUSTAFA ORAL |
| Course Instructor |
Mehmet SARIGÜL
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
Computer vision is needed in Industrial automation systems constantly. Especially applications such as piece counting and quality controls are done with computer vision . The aim of this course, to provide manipulation of images and carry out a computer vision software for an industrial application .
Course Content
Mathematical Image Presentations, Image Sampling, Image Exchanges: Fourier, Karhunen-Loeve, etc.., Image quality enhancement: Statistical Methods, Ad Hoc Techniques, Image Restoration: Inverse Filtering, statistical and algebraic.
Course Precondition
None
Resources
1. GONZALEZ R.C., WOODS R.E., and ADDINS S.L., Digital Image Processing Using Matlab, Pearson Education Inc., New Jersey, 2004.
Notes
1. LOW A., Introductory Computer Vision and Image Processing, McGrow-Hill, 1991, ENGLAND. 2. AWCOCK G.J. and THOMAS R., Applied Image Processing, McGrow-Hill, Inc., 1996. 4. 3. JAHNE B., Digital Image Processing, Springer-Verlag, 2005, Netherlands.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Identify the hardware components of computer vision. |
| LO02 | To have knowledge about image processing. |
| LO03 | Create image processing algorithms and write programs |
| LO04 | To design an industrial vision system. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Adequate knowledge of mathematics, science and related engineering disciplines; ability to use theoretical and applied knowledge in these fields in solving complex engineering problems. | 4 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Ability to identify, formulate and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose. | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose. | 3 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively. | 3 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics. | 4 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Ability to work effectively in interdisciplinary and multidisciplinary teams; individual working skills. | 4 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Ability to communicate effectively verbally and in writing; knowledge of at least one foreign language; ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and understandable instructions. | 5 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Awareness of the necessity of lifelong learning; ability to access information, follow developments in science and technology, and constantly renew oneself. | 2 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Knowledge of ethical principles, professional and ethical responsibility, and standards used in engineering practice. | 5 |
| PLO10 | Bilgi - Kuramsal, Olgusal | Knowledge of business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; knowledge of sustainable development. | 1 |
| PLO11 | Bilgi - Kuramsal, Olgusal | Knowledge of the effects of engineering practices on health, environment and safety in universal and social dimensions and the problems of the age reflected in the field of engineering; awareness of the legal consequences of engineering solutions. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Hardware and Software Structure f oComputer Vision System | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 2 | Image Matrix, the Principles of Neighborhood | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 3 | Gray-Level Image Processing, Binary Image Processing, Color-Image Processing, Differences and Usages | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 4 | Quantization, Thresholding, Histogram, Noise Reduction Techniques | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 5 | Edge Detection, Corner Detection | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 6 | Image Analysis for Pattern Recognition | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 7 | Pixel-Based Operations | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 8 | Mid-Term Exam | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Morphological Operations | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 10 | Image Compression | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 11 | Sample Applications for 1st category- Presentations | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma, Bireysel Çalışma, Proje Temelli Öğrenme , Soru-Cevap |
| 12 | Sample Applications 2nd category - Presentations | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma, Bireysel Çalışma, Proje Temelli Öğrenme , Soru-Cevap |
| 13 | Sample Applications for 3rd category - Presentations | Reading the lecture notes | Öğretim Yöntemleri: Tartışma, Soru-Cevap, Bireysel Çalışma, Proje Temelli Öğrenme |
| 14 | Sample Applications for 4th category - Presentations | Reading the lecture notes | Öğretim Yöntemleri: Tartışma, Alıştırma ve Uygulama |
| 15 | Sample Applications for 5th category- Presentations | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Bireysel Çalışma, Proje Temelli Öğrenme |
| 16 | Term Exams | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||