MECHATRONICS (TURKISH)
Associate	TR-NQF-HE: Level 5	QF-EHEA: Short Cycle	EQF-LLL: Level 5

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
EEE5541	Introduction to Digital Image and Video Processing	Spring Fall	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:	Associate (Short 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)	To improve fundamental computer knowledge, to encourage students using office and package programs.
2)	Ability to have and use of fundamental mathematics knowledge and skills the usage of relevant materials.
3)	Ability to recognize general structures of machine equipments and the features of shaping
4)	Ability to grasp manufacturing processes and cutting tool materials, materials, statics, mechanics and fluid science fundemantal knowledge.
5)	Ability to draw assembly and auxilary devices as well as to draw whole or details of a system.
6)	Ability to have a knowledge of fundemantal manufacturing process such as turning, milling, punching,grinding and welding techniques and to have a self esteem in order to work behind the bench.
7)	Ability to do computer aided design and write program on digital benches.
8)	Ability to prepare project report, follow up project process and implement projects.
9)	ability to learn the areas of usage of electronic circuit components. Ability to grasp and write programs for micro controllers and for their components. Ability to design relevant circuits.
10)	Ability to understand the electric motors principles and AC-DC analysis
11)	Ability to gain a dominaion on visual programming
12)	Having the ability to communicate efficiently in verbal and written Turkish, to know at least one foreign language in order to communicate with the colleagues and customers.