Course Information

Semester	Course Unit Code	Course Unit Title	T+P+L	Credit	Number of ECTS Credits
7	EEE 431	Image Processing	3+0+0	3	5

Course Details

Language of Instruction	English
Level of Course Unit	Bachelor's Degree
Department / Program	Electrical and Electronics Engineering
Mode of Delivery	Face to Face
Type of Course Unit	Elective
Objectives of the Course	The objectives of the course are to gain the ability to improve, segment, represent, identify a recognition problem and to propose a suitable solution to this problem, to gain the ability to design and execute image processing solutions using a software package, to gain the ability to analyze and interpret processed image data, Analyze their limitations and complexity levels, understand the role of image processing solutions in many areas
Course Content	Fundamentals of digital images, Sampling and quantization of images, connectivity, distance measures, arithmetic / logic operations, Contrast diffusion and histogram processing, Other image enhancement techniques, filtering in spatial media, Discrete Fourier transform, 2-D Fourier transform and its properties, fast Fourier transform, Filtering, line and edge extraction in frequency domain Edge binding, thresholding, Optimal thresholding, regional image segmentation, Motion segmentation, color image fundamentals, Color image processing, Image representation techniques, Image recognition techniques, Image recognition methods
Course Methods and Techniques
Prerequisites and co-requisities	( EEM 305 )
Course Coordinator	Instructor Dr. Yalçın ALBAYRAK
Name of Lecturers	Asist Prof.Dr. YALÇIN ALBAYRAK
Assistants	None
Work Placement(s)	No

Recommended or Required Reading

Resources	Digital Image Processing, R.C. Gonzalez, R.E. Woods, Prentice-Hall, 2002

Course Category

Engineering	%90
Science	%10

Planned Learning Activities and Teaching Methods

Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration	Total Work Load
Course Duration	14	3	42
Hours for off-the-c.r.stud	16	3	48
Assignments	2	10	20
Presentation	2	10	20
Mid-terms	1	3	3
Final examination	1	3	3
Total Work Load			Number of ECTS Credits 5 136

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:

No	Learning Outcomes
1	To learn some image basics, contrast enhancement techniques and their use, basic spatial-media filtering, line and edge removal techniques
2	To learn 2-D Fourier transform, its properties and filtering in frequency domain
3	To learn thresholding techniques and basic regional segmentation techniques
4	To learn basic image segmentation, representation, definition and recognition methods
5	Learning the basics of color image processing
6	To propose a solution to a real problem consisting of a range of image processing techniques
7	To interpret and evaluate image processing techniques and algorithms
8	Solving basic image processing exercises using a software package and writing experimental study reports

Weekly Detailed Course Contents

Week	Topics	Study Materials	Materials
1	Fundamentals of digital images	.	.
2	Sampling and quantization of images, connectivity, distance measures, arithmetic / logic operations	.	.
3	Contrast spreading and histogram processing	.	.
4	Other image enhancement techniques, filtering in spatial medium	.	.
5	Discrete Fourier transform, 2-D Fourier transform and its properties, fast Fourier transform	.	.
6	Filtering, line and edge extraction in frequency domain	.	.
7	Edge binding, thresholding	.	.
8	Optimal thresholding, regional image segmentation	.	.
9	Midterm Exam	.	.
10	Motion segmentation, color image basics	.	.
11	Color image processing	.	.
12	Image representation techniques	.	.
13	Image identification techniques	.	.
14	Image recognition methods	.	.

Contribution of Learning Outcomes to Programme Outcomes

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https://obs.akdeniz.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=2429159&lang=en