CENG537 Image and Vision Computing

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code CENG537
Name Image and Vision Computing
Semester . Semester
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 Goal

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