Industrial 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:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Compulsory

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) Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
4) Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively i Turkish, both orally and in writing; knowledge of a minimum of one foreign language.
8) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9) Awareness of professional and ethical responsibility.
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; 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)	Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
2)	Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
3)	Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
4)	Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
5)	Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.
6)	Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7)	Ability to communicate effectively i Turkish, both orally and in writing; knowledge of a minimum of one foreign language.
8)	Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9)	Awareness of professional and ethical responsibility.
10)	Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11)	Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; 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