MOLECULAR BIOLOGY AND GENETICS
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
EEE5541	Introduction to Digital Image and Video Processing	Spring	3	0	3	12

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Dr. Öğr. Üyesi ZAFER İŞCAN
Recommended Optional Program Components:	None
Course Objectives:	This is an introductory course on digital image and video processing designed for graduate students and senior level undergraduate students. The objectives of the course are as follows: To introduce the student to theoretical foundations in Digital Image and Video Processing; to introduce the student to modern applications in Digital Image and Video Processing; to give students a hands-on experience about image and video processing using extensive simulation assignments (mostly using MATLAB); to give students an ability to solve complex engineering problems, that require image and video processing.

Learning Outcomes

The students who have succeeded in this course;
1.Discuss the main processes and problems of image and video formation and reproduction
2.Describe image and video sampling and quantization.
3.Apply functions Image Processing Toolbox in MATLAB to image and video processing problems.
4.Define and compute apply geometric transformations on images.
5.Describe and apply gray level transformations and frequency domain filtering on images and video.
6.Discuss and apply image restoration, morphological image processing, and image segmentation
7.Apply basic image compression and feature extraction approaches.
8.Describe video sampling rate and standards conversion
9.Explain motion estimation, and video enhancement methods.

Course Content

Introduction and overview; Human Visual System,
Image Formation; Image Processing Basics; MATLAB Basics;
Image Processing Toolbox; Image Sensing and Acquisition;
Arithmetic and Logic Operators; Geometric Operators;
Gray-level Transformations; Histogram Processing;
Neighborhood Processing; Frequency Domain Filtering;
Image Restoration; Morphological Image Processing;
Edge Detection; Image Segmentation; Color Image Processing;
Image Compression and Coding; Feature Extraction and Representation, Visual Pattern Recognition; Video Fundamentals, Video Standards, Video Standards Conversion,
Motion Estimation and video enhancement

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction and overview, Human Visual System, Image Formation
2)	Image Processing Basics, MATLAB Basics
3)	MATLAB Image Processing Toolbox, Image Sensing and Acquisition
5)	Gray-level Transformations, Histogram Processing
7)	Edge Detection, Image Segmentation
8)	Image Segmentation, Midterm Exam
9)	Image Restoration, Morphological Image Processing
10)	Color Image Processing
11)	Image Compression and Coding
12)	Feature Extraction and Representation, Visual Pattern Recognition
13)	Video Fundamentals, Video Standards, Video Standards Conversion
14)	Motion Estimation and video enhancement

Sources

Course Notes / Textbooks:	Practical Image and Video Processing Using MATLAB, Oge Marques, Wiley, 2011, ISBN: 978111093467.
References:	Video Processing and Communications, by Yao Wang, Joern Ostermann, and Ya-Qin Zhang, Prentice Hall, 2002, ISBN 0-13-017547-1. Digital Video Processing, by M. Tekalp, Prentice Hall, 1995, ISBN 0-13-190075-7.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	4	% 20
Project	1	% 20
Midterms	1	% 20
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	5	70
Project	1	14	14
Homework Assignments	4	20	80
Midterms	1	3	3
Final	1	3	3
Total Workload			212

Contribution of Learning Outcomes to Programme Outcomes

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

	Program Outcomes	Level of Contribution
1)	Utilize the wealth of information stored in computer databases to answer basic biological questions and solve problems such as diagnosis and treatment of diseases.	3
2)	Acquire an ability to compile and analyze biological information, clearly present and discuss the conclusions, the inferred knowledge and the arguments behind them both in oral and written format.	4
3)	Develop critical, creative and analytical thinking skills.	5
4)	Develop effective communication skills and have competence in scientific speaking, reading and writing abilities in English and Turkish.	3
5)	Gain knowledge of different techniques and methods used in genetics and acquire the relevant laboratory skills.	4
6)	Detect biological problems, learn to make hypothesis and solve the hypothesis by using variety of experimental and observational methods.	4
7)	Gain knowledge of methods for collecting quantitative and qualitative data and obtain the related skills.	3
8)	Conduct research through paying attention to ethics, human values and rights. Pay special attention to confidentiality of information while working with human subjects.	5
9)	Obtain basic concepts used in theory and practices of molecular biology and genetics and establish associations between them.	4
10)	Search and use literature to improve himself/herself and follow recent developments in science and technology.	5
11)	Be aware of the national and international problems in the field and search for solutions.	4