TÜRKÇE
ENGLISH
Information
| Code | CENG537 |
| Name | Image and Vision Computing |
| Term | 2023-2024 Academic Year |
| Term | Fall |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. MUSTAFA ORAL |
| Course Instructor |
1 |
Course Goal / Objective
This course covers the investigation, creation and manipulation of digital images by computer. The course consists of theoretical material introducing the mathematics of images and imaging. Topics include representation of two-dimensional data, time and frequency domain representations, filtering and enhancement, the Fourier transform, convolution, interpolation, color images. The student will become familiar with Image Enhancement, Image Restoration, Wavelets and Multiresolution Processing, Image Compression, Morphological Image Processing, Image Segmentation, Representation and Description, and Object Recognition.
Course Content
Overview, Computer imaging systems;Digital Image Fundamentals;Image enhancement, gray scale mods, histogram mod;Discrete transforms, Fourier; discrete cosine, Walsh-Hadamard, Haar; filtering;Image enhancement, sharpening, smoothing;Image restoration: noise removal: mean, adaptive filters, degradation model, inverse filter; Morphological Image Processing;image compression:lossy and lossless methods;Image Segmentation;Object Recognition.
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. 2. LOW A., Introductory Computer Vision and Image Processing, McGrow-Hill, 1991, ENGLAND. 3. AWCOCK G.J. and THOMAS R., Applied Image Processing, McGrow-Hill, Inc., 1996. 4. JAHNE B., Digital Image Processing, Springer-Verlag, 2005, Netherlands.
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. JAHNE B., Digital Image Processing, Springer-Verlag, 2005, Netherlands.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Can Explain the nature of two dimensional signals, i.e. images. |
| LO02 | to ability to Design and implement solutions for digital image processing problems. |
| LO03 | can compare DIP software development tools |
| LO04 | Be able to discuss the strengths and limitations of DIP applications in solving problems with both professional peers and lay clients. |
| LO05 | Be able to communicate effectively in a project group. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | On the basis of the competencies gained at the undergraduate level, it has an advanced level of knowledge and understanding that provides the basis for original studies in the field of Computer Engineering. | 4 |
| PLO02 | Bilgi - Kuramsal, Olgusal | By reaching scientific knowledge in the field of engineering, he/she reaches the knowledge in depth and depth, evaluates, interprets and applies the information. | 4 |
| PLO03 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the new and developing practices of his / her profession and examining and learning when necessary. | 4 |
| PLO04 | Yetkinlikler - Öğrenme Yetkinliği | Constructs engineering problems, develops methods to solve them and applies innovative methods in solutions. | 5 |
| PLO05 | Yetkinlikler - Öğrenme Yetkinliği | Designs and applies analytical, modeling and experimental based researches, analyzes and interprets complex situations encountered in this process. | 3 |
| PLO06 | Yetkinlikler - Öğrenme Yetkinliği | Develops new and / or original ideas and methods, develops innovative solutions in system, part or process design. | 5 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Has the skills of learning. | 5 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Being aware of new and emerging applications of Computer Engineering examines and learns them if necessary. | 4 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Transmits the processes and results of their studies in written or oral form in the national and international environments outside or outside the field of Computer Engineering. | 2 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Has comprehensive knowledge about current techniques and methods and their limitations in Computer Engineering. | |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Uses information and communication technologies at an advanced level interactively with computer software required by Computer Engineering. | 3 |
| PLO12 | Bilgi - Kuramsal, Olgusal | Observes social, scientific and ethical values in all professional activities. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Overview, Computer imaging systems | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 2 | Digital Image Fundamentals. | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 3 | Image enhancement, gray scale mods, histogram mod | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 4 | Discrete transforms, Fourier | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 5 | discrete cosine, Walsh-Hadamard, Haar, | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 6 | filtering | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 7 | Image enhancement, sharpening, smoothing | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 8 | Mid-Term Exam | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav, Ödev, Performans Değerlendirmesi |
| 9 | Image restoration: noise removal: mean, adaptive filters, degradation model, inverse filter | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 10 | Morphological Image Processing | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 11 | image compression: lossless methods | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 12 | image compression: lossy methods | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 13 | Image Segmentation. | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 14 | Object Recognition. | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 15 | Presentation of term project to class | Reading course material | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 16 | Term Exams | Project design and preparation for the presentation exam | Ölçme Yöntemleri: Sözlü Sınav, Performans Değerlendirmesi, Proje / Tasarım |
| 17 | Term Exams | Project design and preparation for the presentation exam | Ölçme Yöntemleri: Yazılı Sınav, Sözlü Sınav, Ödev, Performans Değerlendirmesi |
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 | ||