Information Systems Engineering
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

FET311

Ders İsmi:

Digital Image Processing

Ders Yarıyılı:

Spring

Ders Kredileri:

Theoretical	Practical	Laboratory	ECTS
2	1	0	5

Language of instruction:

Turkish

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Bölüm Seçmeli

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 :

Asst. Prof. Dr. GÖKALP TULUM

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	Learning and applying the basic concepts of image processing. Contribution of the Course to Professional Sectors: Equipping students with the foundational skills needed to develop applications in professional sectors such as healthcare, defense, and artificial intelligence.
Course Content:	Intensity transformations, contrast enhancement. Geometric transformations, spatial filtering (smoothing and sharpening), and frequency domain analysis. Noise types, noise reduction methods, and inverse filtering techniques. Morphological operations, thresholding, image segmentation, and partitioning techniques.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Performs intensity and geometric transformations of two-dimensional digital images.
2) Performs two-dimensional filtering in the spatial domain.
3) Performs two-dimensional filtering in the frequency domain.
4) Can determine an automatic threshold value to segment an object within an image.
2 - Skills
Cognitive - Practical
1) Can develop practical applications related to image processing topics.
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Fundamentals of Digital Imaging
2)	Intensity Transformations and Contrast Stretching
3)	Geometric Transformation
4)	Spatial Filtering – Smoothing
5)	Spatial Filtering – Sharpening
6)	Frequency Domain – FFT2
7)	Filtering in the Frequency Domain
8)	Noise Types and Averaging Filters
9)	Image Degradation and Inverse Filtering
10)	Morphological Operators
11)	Morphological Operators
12)	Thresholding
13)	Image Segmentation
14)	Image Segmentation

Sources

Course Notes / Textbooks:	Gonzalez, Rafael C., Richard E. Woods, and Barry R. Masters. "Digital image processing." (2009): 029901-029901.
References:	Gonzalez, Rafael C., Richard E. Woods, and Barry R. Masters. "Digital image processing." (2009): 029901-029901.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3	4	5
Program Outcomes
1) Adequate knowledge in the fields of mathematics and science; ability to use theoretical and practical knowledge in these fields
2) Adequate knowledge in subjects specific to the relevant engineering discipline; ability to use theoretical and applied knowledge in these areas to solve complex engineering problems.
3) Ability to identify, formulate and solve complex engineering problems.
4) Ability to select and apply appropriate analysis and modeling methods to complex engineering problems.
5) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements.
6) Ability to apply modern design methods to design a complex system, process, device or product.
7) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice.
8) Ability to use information technologies effectively to analyze and solve complex problems encountered in engineering applications.
9) Ability to design and conduct experiments to investigate complex engineering problems or discipline-specific research topics.
10) Ability to collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics.
11) Ability to work effectively in disciplinary teams.
12) Ability to work effectively in multidisciplinary teams.
13) Ability to work individually.
14) Ability to communicate effectively both orally and in writing.
15) Knowledge of at least one foreign language.
16) Effective report writing and comprehension of written reports, ability to prepare design and production reports.
17) Ability to make effective presentations, give and receive clear and understandable instructions.
18) Awareness of the necessity of lifelong learning.
19) Ability to access information, to follow developments in science and technology and to continuously renew oneself.
20) Knowledge about acting in accordance with ethical principles, professional and ethical responsibility and standards used in engineering practices.
21) Knowledge of business practices such as project management, risk management and change management.
22) Awareness about entrepreneurship and innovation.
23) Knowledge about sustainable development.
24) Knowledge about the effects of engineering applications on health, environment and safety in universal and social dimensions and the problems of the era reflected in the field of engineering.
25) Awareness of the legal implications of engineering solutions.

Ders - Öğrenme Kazanımı İlişkisi

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Adequate knowledge in the fields of mathematics and science; ability to use theoretical and practical knowledge in these fields
2)	Adequate knowledge in subjects specific to the relevant engineering discipline; ability to use theoretical and applied knowledge in these areas to solve complex engineering problems.
3)	Ability to identify, formulate and solve complex engineering problems.
4)	Ability to select and apply appropriate analysis and modeling methods to complex engineering problems.
5)	The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements.	5
6)	Ability to apply modern design methods to design a complex system, process, device or product.	5
7)	Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice.	5
8)	Ability to use information technologies effectively to analyze and solve complex problems encountered in engineering applications.	4
9)	Ability to design and conduct experiments to investigate complex engineering problems or discipline-specific research topics.	4
10)	Ability to collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics.	4
11)	Ability to work effectively in disciplinary teams.	3
12)	Ability to work effectively in multidisciplinary teams.
13)	Ability to work individually.
14)	Ability to communicate effectively both orally and in writing.
15)	Knowledge of at least one foreign language.
16)	Effective report writing and comprehension of written reports, ability to prepare design and production reports.
17)	Ability to make effective presentations, give and receive clear and understandable instructions.
18)	Awareness of the necessity of lifelong learning.
19)	Ability to access information, to follow developments in science and technology and to continuously renew oneself.
20)	Knowledge about acting in accordance with ethical principles, professional and ethical responsibility and standards used in engineering practices.
21)	Knowledge of business practices such as project management, risk management and change management.
22)	Awareness about entrepreneurship and innovation.
23)	Knowledge about sustainable development.
24)	Knowledge about the effects of engineering applications on health, environment and safety in universal and social dimensions and the problems of the era reflected in the field of engineering.
25)	Awareness of the legal implications of engineering solutions.

Assessment & Grading

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