CENG376 Image ProcessingIstanbul Okan UniversityDegree Programs Computer Engineering (English)General Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Computer Engineering (English)
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

General course introduction information

Course Code: CENG376
Course Name: Image Processing
Course Semester: Fall
Course Credits:
Theoretical Practical Credit ECTS
3 0 3 7
Language of instruction: EN
Course Requisites:
Does the Course Require Work Experience?: No
Type of course: Department Elective
Course Level:
Bachelor TR-NQF-HE:6. Master`s Degree QF-EHEA:First Cycle EQF-LLL:6. Master`s Degree
Mode of Delivery: Face to face
Course Coordinator : Prof. Dr. BEKİR TEVFİK AKGÜN
Course Lecturer(s): Öğr.Gör. KÜBRA CENGİZ
Course Assistants:

Course Objective and Content

Course Objectives: The aim of this course is to teach students the theoretical foundations of digital image processing and to introduce their modern applications.
Course Content: Understanding the basic components of an image processing system.
How images are represented; Understanding including optical images, analog and digital images. Understanding image types such as dual image, gray scale image, color image, and multi-spectrum image.
Understanding why preprocessing is done; having information about image geometry, convolution masks, image algebra and basic spatial filters.
Understanding image quantization in both spatial and brightness domains.
Understanding how discrete transforms work.
Understanding low pass, high pass, band pass and notch filters.
Understanding the three categories of image processing applications: improvement, repair and compression.

Learning Outcomes

The students who have succeeded in this course;
Learning Outcomes
1 - Knowledge
Theoretical - Conceptual
1) To understand the basic concepts of digital image processing systems.
2) To be able to recognize and use the similarities between one and two dimensional signal analysis and processing.
2 - Skills
Cognitive - Practical
1) To analyze two-dimensional signals in the frequency domain by Fourier transform.
2) Designing and applying algorithms for digital image processing operations.
3 - Competences
Communication and Social Competence
Learning Competence
1) Evaluate and compare the performance of digital image processing operations.
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week Subject Related Preparation
1) Introduction and Motivation None
2) Visual perception, Light and Electromagnetic spectrum, Math model of image, Image perception and acquisition Course notes
3) Linear systems, Convolution, Correlation, Impulse response Course notes
4) Fourier transform and its properties, Concept of frequency in the image and frequency spectrum of the image, Sampling of the image, conditions on the overlap and sampling frequency, Creation of the image from sinusoidal planar waves Course notes
5) Fourier transform and its properties Course Notes
6) Image enhancement in spatial domain: Pixel-point operations such as lighting, dimming and contrast modification (histogram stretching, equalization, indication etc.) Course notes
7) Image enhancement in spatial domain: Pixel-group operations such as convolution, convolution mask-related operations Course notes
8) Midterm None
9) Image improvement in frequency domain Course Notes
10) Image enhancement in frequency domain Course notes
11) Edging (Prewitt, Roberts, Sobel, Laplacian, Canny, Hoteling) Course notes
12) Morphological operations Course notes
13) Color image processing Course notes
14) Color image processing Course notes
15) Final Exam None

Sources

Course Notes / Textbooks: R. C. Gonzalez, R. E. Woods, Digital Image Processing, 4th edition, Pearson, 2017.

References: A. K. Jain, Fundamentals of Digital İmage Processing, Prentice Hall, Addison-Wesley, 1989.

Course-Program Learning Outcome Relationship

Learning Outcomes

1

2

3

4

5

Program Outcomes
1) Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2) The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
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. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5) Ability to design experiments, conduct experiments, collect data, analyze and interpret results for examination of engineering problems.
6) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7) Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge.
8) Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Professional and ethical responsibility.
10) Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
11) Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions.

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2) The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
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. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5) Ability to design experiments, conduct experiments, collect data, analyze and interpret results for examination of engineering problems.
6) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7) Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge.
8) Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Professional and ethical responsibility.
10) Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
11) Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions.

Learning Activity and Teaching Methods

Expression
Brainstorming/ Six tihnking hats
Individual study and homework
Lesson
Reading
Project preparation
Q&A / Discussion
Case Study

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Individual Project

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Project 1 % 20
Midterms 1 % 30
Final 1 % 50
total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
total % 100

Workload and ECTS Credit Grading

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Project 1 40 40
Midterms 1 50 50
Final 1 70 70
Total Workload 202